The 6th World Conference on Soft Computing

dedicated to

50th Anniversary of

Fuzzy Logic and Its Applications and

95th Birthday Anniversary of

Lotfi A. Zadeh

University of California, Berkeley, California

PROGRAM

organized and sponsored by

MINISTRY OF COMMUNICATIONS AND HIGH TECHNOLOGIES

OF THE REPUBLIC OF AZERBAIJAN

May 22-25, 2016 Berkeley, CA, USA

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Table of Contents

Organizers ………………………………………………………………………. 5

Program Committee …………………………………………………………. 9

Schedule at Glance………………………………………………………….. 11

Sunday …………………………………………………………………………… 15

Monday Sessions ……………………………………………………………. 17

Tuesday Sessions……………………………………………………………. 23

Wednesday Sessions………………………………………………………. 29

Plenary Talks………………………………………………………………….. 33

Venue …………………………………………………………………………… 53

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Organizers

Honorary Conference Chairs Lotfi A. Zadeh University of California, Berkeley

Ali M. Abbasov National Academy of Sciences of the Republic of Azerbaijan, Azerbaijan

General Chair Shahnaz N. Shahbazova Azerbaijan Technical University, Azerbaijan

General Co-Chairs Vladik Kreinovich University of Texas at El Paso, USA

Marek Z. Reformat University of Alberta, Canada

Ronald R. Yager Iona College, New York

Advisory Co-Chairs Ildar Batyrshin National Polytechnic Institute, Mexico László T. Kóczy Budapest University of Technology and Economics, Budapest, Hungary William Melek University of Waterloo, Canada Vadim Stefanyuk Russian Academy of Sciences, Russia

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Program Co-Chairs Janusz Kacprzyk Systems Research Institute, Polish Academy of Sciences, Poland

Vladik Kreinovich University of Texas at El Paso, USA

Marek Z. Reformat University of Alberta, Canada

Special Sessions Co-Chair Ashok Deshpande Pune University, India

Fernando Gomide University of Campinas, Brazil Publicity Chair Vladik Kreinovich University of Texas at El Paso, USA

Local Organizing Co-Chairs Shahnaz N. Shahbazova Azerbaijan Technical University, Azerbaijan

Sabina S. Shahbazzade UC Berkeley, USA

Chimnaz S. Shahbazzade UC Berkeley, USA

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Program Committee

Ajith Abraham (USA)

Rafiq Aliev (Azerbaijan) Alekber Aliyev (Azerbaijan)

Fikret Aliyev (Azerbaijan) Telman Aliyev (Azerbaijan) Rasim Alquliev (Azerbaijan)

Mehdi Bahrami (USA) Andrzej Bargiela (UK)

Joe Barone (USA) Mokhtar Beldjehem (Canada)

Hamid Berenji (USA) Michael Berthold (Germany)

Jim Bezdek (USA) Piero Bonissone (USA)

Bernadette Bouchon-Meunier (France) Christer Carlsson (Finland)

Joao Carvalho (Portugal) Oscar Castillo (Mexico) Guoqing Chen (China)

Valerie Cross (USA) Bernard deBaets (Belgium)

Miguel Delgado (Spain) Ramon Lopez deMantaras (Spain)

Didier Dubois (France) Jozo Dujmovic (USA)

Dimitar Filev (USA) Fernando Gomide (Brasil)

William Gruver (USA) Madan Gupta (Canada)

Asaf Hajiyev (Azerbaijan) Larry Hall (USA)

Kaoru Hirota (Japan) Eyke Hullermeier (Germany)

Ismail Ibrahimov (Azerbaijan) Mo Jamshidi (USA)

Janusz Kacprzyk (Poland) Abe Kandel (USA)

Jim Keller (USA) Etienne Kerre (Belgium) Peter Klement (Austria)

László T. Kóczy (Hungary) Bart Kosko (USA)

Vladek Kreinovich (USA) Henrik Larsen (Denmark)

Chang-Shing Lee (Taiwan)

Jonathan Lee (Taiwan) Chin-Teng Lin (Taiwan) T.Y. Lin (USA) Vincenzo Loia (Italy) Luis Magdalena (Spain) Trevor Martin (UK) Agassi Melikov (Azerbaijan) Jerry Mendel (USA) Javier Montero (Spain) Hung Nguyen (USA) Vesa Niskanen (Finland) Vilem Novak (Czech Republic) Nikhil K. Pal (India) Sankar R. Pal (India) Gabriella Pasi (Italy) Witold Pedrycz (Canada) Irina Perfilieva (Czech Republic) Fred Petry (USA) Henri Prade (France) Rovshan Quliyev (Azerbaijan) Anca Ralescu (USA) Dan Ralescu (USA) Marek Reformat (Canada) Rita Ribeiro (Portugal) Enrique Ruspini (Spain) Rudi Seising (Spain) Glenn Shafer (USA) Shahnaz Shahbazova (Azerbaijan) Tom Sudkamp (USA) Michio Sugeno (Japan) Eulelia Szmidt (Poland) Tomohiro Takagi (Japan) Settimo Termini (Italy) Enric Trillas (Spain) I.Burhan Turksen (Turkey) Aldo Ventre (Italy) Jose Luis Verdegay (Spain) Carol Walker (USA) Elbert Walker (USA) Paul Wang (USA) Bernard Widrow (USA) Ronald R. Yager (USA) Hao Ying (USA) Slawomir Zadrozny (Poland) Hans Zimmermann (Germany)

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Schedule at Glance Sunday, May 22th 2016 Time: 6:00pm - 8:00pm

Welcome Reception Location: Auditorium, International House UC Berkeley

2299 Piedmont Ave, Berkeley, CA 94720

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Monday, May 23rd 2016 Location: International House UC Berkeley

8:00am 9:00am Registration

8:30am 9:00am Opening

9:00am 9:45am

Stratification, target set reachability and incremental enlargement principle Lotfi A. Zadeh

Auditorium

9:45am 10:30am

Issues in Multi-Criteria Decision Making Ronald R. Yager

Auditorium 10:30am 10:45am Coffee Break

10:45am 11:45am

Fuzzy Modeling and Cognitive Maps

Auditorium

Clustering and Classification Ida Sproul Room

Novel Population-based Optimization Algorithms

Robert Sproul Room

11:45am 12:45pm

Fundamentals of Fuzzy Sets I

Auditorium

Fuzziness and Health Care Ida Sproul Room

Ensemble Neural Networks Robert Sproul Room

12:45pm 2:00pm Lunch

2:00pm 3:00pm

Fundamentals of Fuzzy Sets II

Auditorium

Image Analysis and Character Recognition

Ida Sproul Room

Fuzzy Control Robert Sproul Room

3:00pm 3:45pm

Soft Computing: Philosophical, Mathematical, and Theoretical Foundations of Cognitive Robotics and Computational Intelligence

Yingxu Wang Auditorium

3:45pm 4:00pm Coffee Break

4:00pm 4:45pm

Perspectives on Type-2 fuzzy Sets and Systems Jerry M. Mendel

Auditorium

4:45pm 5:30pm

Systems Intelligence in Healthcare – Changes in Lifestyle Behavior and Vitals Hiroshi Nakajima

Auditorium

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Tuesday, May 24th 2016 Location: International House UC Berkeley

9:00am 9:45am

Decomposable Graphical Models: On Learning, Fusion and Revision Rudolf Kruse

Auditorium

9:45am 10:30am

Fuzzy and cognitive approaches of similarities Bernadette Bouchon-Meunier

Auditorium 10:30am 10:45am

Coffee Break

10:45am 11:45am

Fuzziness in Civil and Environmental

Engineering I Auditorium

Web Applications Ida Sproul Room

Optimization Algorithms and Time Series Prediction

Robert Sproul Room

11:45am 12:45pm

Fuzziness in Civil and Environmental

Engineering II Auditorium

Data Analysis Ida Sproul Room

Fuzziness in Pedagogy Robert Sproul Room

12:45pm 2:00pm Lunch

2:00pm 3:00pm

Fuzziness in Civil and Environmental

Engineering III Auditorium

Text and Information Processing

Ida Sproul Room

Experts, Games and Games-inspired Methods

Robert Sproul Room

3:00pm 3:45pm

Recognition Technology: Lotfi’s look to the future from the late 1990s James M. Keller

Auditorium 3:45pm 4:00pm Coffee Break

4:00pm 4:45pm

From Fuzzy Sets to Spatial Cognition Christian Freksa

Auditorium Time: 7:00pm – 10:00pm

Banquet Location: Double Tree by Hilton, Berkeley Marina Transportation: Shuttle service around 6:30pm from Downtown Berkeley BART station

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Wednesday, May 25th 2016

Location: International House UC Berkeley

9:00am 9:45am

Fuzzy preferences and majority in multiagent decision making: from status quo to innovative decisions

Janusz Kacprzyk Auditorium

9:45am 10:30am

Fuzzy Logic Can Justify and Improve Semi-Heuristic Data and Image Processing Techniques: Main Idea and Case Studies

Vladik Kreinovich Auditorium

10:30am 10:45am

Coffee Break

10:45am 11:45am

Fuzzy-inspired Approaches Auditorium

Shape Extraction and Edge Detection

Ida Sproul Room

Scheduling, Selection and Impact Evaluation

Robert Sproul Room

11:45am 12:45pm

Optimization, Decision Making and Estimation

Auditorium

Classification and Hierarchical Modeling

Ida Sproul Room

Fuzziness in Human and Resource Management

Robert Sproul Room

12:45pm 2:00pm Lunch

2:00pm 2:45pm

Fuzzy Logic and Non-Statistical Association Measures Ildar Batyrshin

Auditorium 2:45pm 3:00pm Coffee Break

3:00pm 3:45pm

Explorations in Ordinal Preference Theory with the Savage’s Omelet Problem Michio Sugeno

Auditorium

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Sunday May 22nd, 2016

Time: 6:00pm - 8:00pm

Welcome Reception Location: Auditorium, International House UC Berkeley

2299 Piedmont Ave, Berkeley, CA 94720

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Monday May 23rd, 2016

Time : 8:00am – 9:00am Registration & Opening Location: Auditorium, International House UC Berkeley Time : 9:00am – 10:30am Stratification, target set reachability and incremental enlargement principle Lotfi A. Zadeh

Issues in Multi-Criteria Decision Making Ronald R. Yager Chair: Janusz Kacprzyk Location: Auditorium Time : 10:30am – 10:45am COFFEE BREAK

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Time : 10:45am – 11:45am Fuzzy Modeling and Cognitive Maps Chair:  Hiroshi Nakajima  Location: Auditorium Room Participatory Search Algorithms in Fuzzy Modeling Yi Ling Liu, Fernando Gomide Fuzzy Physiologically Based Pharmacokinetic (PBPK) Model of Chloroform in Swimming Pools R. A. Dyck, R. Sadiq, M.J. Rodriguez Fuzzy Cognitive Maps models and formulas Chrysostomos Stylios

Clustering and Classification Chair: Yingxu Wang  Location: Ida Sproul Room An Energy Aware Approach for Unequal Clustering using Fuzzy System in Wireless Sensor Networks Ali Asghar Rahmani Hosseinabadi, Maryam Kardgar, Hamed Ebadi, Valentina Emilia Balas Evaluating Multi-criteria Flight Reviews with Similarity-based Clustering Ibrahim Yakut, Tugba Turkoglu Study of Soft Computing methods for large-scale multinomial malware types and families detection Lars Strande Grini, Andrii Shalaginov, Katrin Franke Novel Population-based Optimization Algorithms Chair: Jerry Mendel Location: Robert Sproul Room Bio-inspired optimization metaheuristic algorithm based on the self-defense of the plants Camilo Caraveo, Fevrier Valdez, Oscar Castillo Experimenting with a New Population-Based Optimization Technique: FUNgal Growth Inspired (FUNGI) Optimizer Alex Tormási, László T. Kóczy A Hybrid Genetic Algorithm for Minimum Weight Dominating Set Problem O. Ugurlu, D. Tanir

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Time : 11:45am – 12:45pm Fundamentals of Fuzzy Sets I Chair: Jozo Dujmović Location: Auditorium Fuzzy Objects in Sets with similarities and Powerset Operators Jiri Mockor Towards real-time Lukasiewicz Fuzzy Systems Barnabas Bede, Imre J. Rudas Complex Number Representation of Intuitionistic Fuzzy Sets Dan E. Tamir, Mumtaz Ali, Naphtali D. Rishe, Abraham Kandel Fuzziness and Health Care Chair: Marek Reformat Location: Ida Sproul Room Estimating the membership function of the fuzzy willingness-to-pay/accept for health via Bayesian modeling Michal Jakubczyk Fuzzy Logic Based Simulation of Gynaecology Disease Diagnosis A.S. Sardesai, V.S. Kharat, A.W. Deshpande, P.W. Sambarey An ontology for wearables data interoperability and Ambient Assisted Living application development Natalia Diaz-Rodriguez, Stefan Gronroos, Frank Wickstrom, Johan Lilius, Henk Eertink, Andreas Braun, Paul Dillen, James Crowley, Jan Alexandersson Ensemble Neural Networks Chair: Vladik Kreinovich Location: Robert Sproul Room Optimization of Ensemble Neural Networks with Type-1 and Type-2 Fuzzy Integration for Prediction of the Taiwan Stock Exchange Martha Pulido, Patricia Melin Optimization of Modular Neural Network Architectures with an Improved Particle Swarm Optimization Algorithm Alfonso Uriarte, Patricia Melin, Fevrier Valdez Ensemble neural network with type-2 fuzzy weights using response integration for time series prediction Fernando Gaxiola, Patricia Melin, Fevrier Valdez, Juan R. Castro Time : 12:45pm – 2:00pm LUNCH

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Time : 2:00pm - 3:00pm Fundamentals of Fuzzy Sets II Chair: Ildar Batyrshin Location: Auditorium Gamma Aggregators and Extended Generalized Conjunction/Disjunction Jozo Dujmovic Rankings and Total Orderings on Sets of Generalized Fuzzy Numbers Li Zhang, Zhenyuan Wang Game Approach to Fuzzy Measurement V.L. Stefanuk Image Analysis and Character Recognition Chair: Shahnaz Shahbazova Location: Ida Sproul Room Why Sparse? Fuzzy Techniques Explain Empirical Efficiency of Sparsity-Based Data- and Image-Processing Algorithms Fernando Cervantes, Brian Usevitch, Leobardo Valera, Vladik Kreinovich What makes an edge in human and computer vision? A fuzzy spatial-taxon approach Lauren Barghout Probabilistic Rough Sets in Turkish Optical Character Recognition B. Magden, S. Telceken Fuzzy Control Chair: Vladik Kreinovich Location: Robert Sproul Room Statistical Comparison of the Fuzzy BCO and BCO algorithms for Fuzzy Controller Design using Trapezoidals MFs Leticia Amador-Angulo, Oscar Castillo Load Frequency Control of Hydro-Hydro System with Fuzzy Logic Controller Considering Non-Linearity K. Jagatheesan, B. Anand, Nilanjan Dey, Amira S. Ashour, Valentina E. Balas Evolutionary Algorithm tuned Fuzzy PI Controller for a Networked HVAC System Narendra Kumar Dhar, Nishchal K. Verma, Laxmidhar Behera

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Time : 3:00pm – 3:45pm Soft Computing: Philosophical, Mathematical, and Theoretical Foundations of Cognitive Robotics and Computational Intelligence Yingxu Wang Chair: Shahnaz Shahbazova Location: Auditorium Time : 3:45pm - 4:00pm COFFEE BREAK Time : 4:00pm – 5:30pm Perspectives on Type-2 fuzzy Sets and Systems Jerry M. Mendel

Systems Intelligence in Healthcare – Changes in Lifestyle Behavior and Vitals Hiroshi Nakajima Chair: Ron Yager Location: Auditorium

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Tuesday May 24th, 2016

Time : 9:00am – 10:30am Decomposable Graphical Models: On Learning, Fusion and Revision Rudolf Kruse

Fuzzy and cognitive approaches of similarities Bernadette Bouchon-Meunier Chair: Shahnaz N. Shahbazova Location: Auditorium Time : 10:30am – 10:45am COFFEE BREAK

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Time : 10:45am – 11:45am Fuzziness in Civil and Environmental Engineering I Chair: Rudolf Kruse Location: Auditorium How to Estimate Resilient Modulus for Unbound Aggregate Materials: A Theoretical Explanation of an Empirical Formula Pedro Barragan Olague, Soheil Nazarian, Vladik Kreinovich, and Afshin Gholamy, Mehran Mazari Genetic Algorithm-based Neural Network for Scour Depth Prediction at 45° Wing-wall Abutment Abul Kashim Md Fujail, Shahin Ara Begum, Abdul Karim Barbhuiya Development of NARX based neural network models for predicting air quality near busy urban corridors Rohit Jaikumar, S.M. Shiva Nagendra, R. Sivanandan Recommendation and Retrieval Chair: Jim Keller Location: Ida Sproul Room A Survey of the Applications of Fuzzy Methods in Recommender Systems B. Szi, Alex Tormasi, P. Foldesi, Laszlo T. Koczy Aspect Ranking based on Domain Relevance: Its Analysis & Applications Sheikh Amanur Rahman, M. M. Sufyan Beg Personalization and Optimization of Information Retrieval: Adaptive Semantic Layer Approach Alexander Ryjov Optimization Algorithms and Time Series Prediction Chair: Bernadette Bouchon-Meunier  Location: Robert Sproul Room Dynamic parameter adaptation in the Chemical Reaction Algorithm using Type-2 Fuzzy Logic David de la O, Oscar Castillo, Jose Soria Optimization of a Tracking Controller for Mobile Robots Based on the Chemical Reaction Algorithm David de la O, Oscar Castillo, Jose Soria Particle Swarm Optimization of Fuzzy Integration in Ensembles of ANFIS Models for Time Series Prediction Jesus Soto, Patricia Melin, Oscar Castillo

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Time : 11:45am – 12:45pm Fuzziness in Civil and Environmental Engineering II Chair: Ashok Deshpande Location: Auditorium How to Predict Nesting Sites and How to Measure Shoreline Erosion: Fuzzy and Probabilistic Techniques for Environment-Related Spatial Data Processing Stephen M. Escarzaga, Craig Tweedie, Olga Kosheleva, Vladik Kreinovich Analysis and Control of Coagulation of a Water Treatment System Using Neuro-Fuzzy Logic: A study applied to the Water Treatment Plant of Sorocaba S. Moroizumi, Monteiro Masalskiene Roveda, J.A.F. Roveda Comparison of fuzzy synthetic evaluation techniques for evaluation of air quality: a case study Hrishikesh Chandra Gautam, S.M. Shiva Nagendra Data Analysis Chair: lldar Batyrshin  Location: Ida Sproul Room Frequent Itemset Mining for a Combination of Certain and Uncertain Databases Samar Wazir, Tanvir Ahmad, M.M. Sufyan Beg Multiset Approach to Compare Qualitative Data Maciej Krawczak, Grazyna Szkatula A New Method for Filling Missing Value Based on the Rough Set Theory R. Cekik, S. Telceken Fuzziness in Pedagogy Chair: Fernando Gomide  Location: Robert Sproul Room Optimal ranking of factors affecting students’ academic performance based on belief and plausibility measures Satish S. Salunkhe, Yashwant Joshi, Ashok Deshpande Bilingual Students Benefit from Using Both Languages Julian Viera, Olga Koshelevaa, Shahnaz N. Shahbazova Optimal academic ranking of students in a Fuzzy Environment: A Case Study Satish S. Salunkhe, Yashwant Joshi, Ashok Deshpande Time : 12:45pm – 2:00pm LUNCH

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Time : 2:00pm - 3:00pm Fuzziness in Civil and Environmental Engineering III Chair: Christian Freska Location: Auditorium Evaluation of Green Spaces Using Fuzzy Systems M.T. Mota, Monteiro Masalskiene Roveda, J.A.F. Roveda A New Methodology for Application of Impact’s Identification Using Fuzzy Relation J.A.F.Roveda, Do Amaral Burghi, Monteiro Masalskiene Roveda, A. Bressane, L.V.G. Franca Sustainability Index: A fuzzy Approach for a municipal decision support system Da Silva Soares, Monteiro Masalskiene Roveda, J.A.F. Roveda, W.A. Lodwick Text and Information Processing Chair: Vadim Stefanyuk Location: Ida Sproul Room A Hierarchy-Aware Approach to the Multiaspect Text Categorization Problem Slawomir Zadrozny, Janusz Kacprzyk, Marek Gajewski Adaptive Neuro-Fuzzy Inference System for Classification of Texts Aida-Zade Kamil, Samir Rustamov, Mark A. Clements, Elshan Mustafayev Big Data Analytics and Fuzzy Technology: Extracting Information from Social Data Sabina Shahbazzade, Shahnaz N. Shahbazova Experts, Games and Game-inspired Methods Chair: Valentina Emilia Balas  Location: Robert Sproul Room How to Describe Measurement Uncertainty and Uncertainty of Expert Estimates? Nicolas Madrid, Irina Perfilieva, Vladik Kreinovich Jagdambika method for solving matrix games with fuzzy payoffs Tina Verma, Amit Kumar Discrimination of Electroencephalograms on Recognizing and Recalling Playing Cards -A Magic without Trick- T. Yamanoi, H. Toyoshima, H. Takayanagi, T. Yamazaki, S. Ohnishi, M. Sugeno

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Time : 3:00pm – 3:45pm Recognition Technology: Lotfi’s look to the future from the late 1990s James M. Keller Chair: Marek Reformat Location: Auditorium Time : 3:45pm – 4:00pm COFFEE BREAK Time : 4:00pm – 4:45pm From Fuzzy Sets to Spatial Cognition Christian Freksa Chair: Marek Reformat Location: Auditorium Time : 7:00pm – 10:00pm

Banquet Location: Double Tree by Hilton, Berkeley Marina Transportation: Shuttle service around 6:30pm from Downtown Berkeley BART station

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Wednesday May 25th, 2016

Time : 9:00am – 10:30am Fuzzy preferences and majority in multiagent decision making: from status quo to innovative decisions Janusz Kacprzyk

Fuzzy Logic Can Justify and Improve Semi-Heuristic Data and Image Processing Techniques: Main Idea and Case Studies Vladik Kreinovich Chair: Ronald R. Yager Location: Auditorium Time : 10:30am – 10:45am COFFEE BREAK

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Time : 10:45am – 11:45am Fuzzy-inspired Approaches Chair: Ron Yager Location: Auditorium Chemical Kinetics in Situations Intermediate Between Usual and High Concentrations: Fuzzy-Motivated Derivation of the Formulas Olga Kosheleva, Vladik Kreinovich, Laecio Carvalho Barros "How to Make a Solution to a Territorial Dispute More Realistic: Taking into Account Uncertainty, Emotions, and Step-by-Step Approach" Mahdokht Afravi, Vladik Kreinovich Fuzzy Scoring of Behavioral Interviews Based on Storytelling Approach D. Balas-Timar, V. E. Balas, M.M. Balas, V. Rao Shape Extraction and Edge Detection Chair: Marek Reformat Location: Ida Sproul Room Pipelined Hardware Architecture for a Fuzzy Logic Based Edge Detection System Aous H. Kurdi, Janos L. Grantner A Quantitative Assessment of Edge Preserving Smoothing Filters for Edge Detection Huseyin Gunduz, Cihan Topal, Cuneyt Akinlar A Fuzzy Shape Extraction Method Annamária R. Várkonyi-Kóczy, B. Tusor, J.T. Toth Scheduling, Selection and Impact Evaluation Chair: Michio Sugeno  Location: Robert Sproul Room The Hybrid Swarm Intelligence Algorithm for The Container Truck Scheduling Problem of Wharfs Yi Liu, Yang Jie Fuzzy Informative Evidence Theory & Application in Project Selection Problem Tanmoy Som, Tuli Bakshi, Arindam Sinharay Mamdani-Type Fuzzy Inference System for Evaluation of Tax Potential Akif Musayev, Shahzade Madatova, Samir Rustamov

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Time : 11:45am – 12:45pm Optimization, Decision Making and Estimation Chair: Ildar Batyrshin Location: Auditorium Structural and Parametric Optimization of Fuzzy Control and Decision Making Systems Yuriy P. Kondratenko, Dan Simon Make decisions based on Evolutionary Computation and Genetic Programming Zafar Jafarov Estimation of Stability of barrels to Vibrating Cavitation on the Basis of the Integrated Deterioration Indicator Ch.M. Aliyev, Z.Z. Sharifov Classification and Hierarchical Modeling Chair: Shahnaz Shahbazova Location: Ida Sproul Room Fuzzy Tolerance Relation Based Hierarchical Community Detection Chengjin Yu, Shu Zhao, Jie Chen, Yanping Zhang, Tingting Zheng, Feng Liu Automatic Image Classification for Web Content Filtering: New Dataset Evaluation V.P. Fralenko, R.E. Suvorov, I.A. Tikhomirov Differentiations in Hierarchical Fuzzy Systems Begum Mutlu, Ebru A. Sezer Fuzziness in Human and Resource Management Chair: Vadim Stefanyuk Location: Robert Sproul Room Resource Selection with Soft Set Attribute Reduction Based on Improved Genetic Algorithm Absalom E. Ezugwu, Shahnaz N. Shahbazova, Aderemi O. Adewumi, Sahalu B. Junaidu Fuzzy multi-criteria method to support group decision making in human resource management M. H. Mammadova, Z. Q. Jabrayilova Fuzzy management of imbalance between supply and demand for IT specialists M. H. Mammadova, Z. Q. Jabrayilova, F.R. Mammadzada Time : 12:45pm – 2:00pm LUNCH

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Time : 2:00pm – 2:45pm Fuzzy Logic and Non-Statistical Association Measures Ildar Batyrshin Chair: Michio Sugeno Location: Auditorium Time : 2:45pm – 3:00pm COFFEE BREAK Time : 3:00pm – 3:45pm Explorations in Ordinal Preference Theory with the Savage’s Omelet Problem Michio Sugeno Chair: Ron Yager Location: Auditorium

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Plenary Talks

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Stratification, target set reachability and incremental enlargement principle

Lotfi A. Zadeh

Department of Electrical Engineering and Computer Sciences

University of California Berkeley, CA 94720-1776

Abstract: This talk presents a brief exposition of a version of the concept of stratification, call it CST for short. In our approach to stratification, CST is a computational system in which the objects of computation are strata of data. Usually, the strata are nested or stacked with nested strata centering on a target set, T. CST has a potential for significant applications in planning, robotics, optimal control, pursuit, multiobjective optimization, exploration, search and other fields. Very simple, familiar examples of stratification are dictionaries, directories and catalogues. A multi-layer perceptron may be viewed as a system with a stratified structure. In spirit, CST has similarity to dynamic programming (DP), but it is much easier to understand and much easier to implement. An interesting question which relates to neuroscience is: Does the human brain employ stratification to store information? It would be natural to represent a concept such as chair, as a collection of strata with one or more strata representing a type of chair. Underlining our approach is a model, call it FSM. FSM is a discrete-time, discrete-state dynamical system which has a finite number of states. The importance of FSM as a model derives from the fact that through the use of granulation and/or quantization almost any kind of system can be approximated to by a finite state system. A concept which plays an important role in our approach is that of target set reachability. Reachability involves moving (transitioning) FSM from a state w to a state in target state, T, in a minimum number of steps. To this end, the state space, W, is stratified through the use of what is refer as the incremental enlargement principle. It should also be noted that the concept reachability is related to the concept of accessibility in modal logic.

Lotfi A. Zadeh joined the Department of Electrical Engineering at the University of California, Berkeley, in 1959, and served as its chairman from 1963 to 1968. Earlier, he was a member of the electrical engineering faculty at Columbia University. In 1956, he was a visiting member of the Institute for Advanced Study in Princeton, New Jersey. In addition, he held a number of other visiting appointments, among them a visiting professorship in Electrical Engineering at MIT in 1962 and 1968; a visiting scientist appointment at IBM Research Laboratory, San Jose, CA, in 1968, 1973, and 1977; and visiting scholar appointments at the AI Center, SRI International, in 1981, and at the Center for the Study of Language and Information, Stanford University, in 1987-1988. Currently he is a Professor in the Graduate School, and is serving as the Director of BISC (Berkeley Initiative in Soft Computing). Until 1965, Dr. Zadeh's work had been centered on system theory and decision analysis. His 1965 paper on fuzzy sets has received over 26,000 Google Scholar citations and is by far the highest cited paper in Information and Control. Since

1965, his research interests have shifted to the theory of fuzzy sets and its applications to artificial intelligence, linguistics, logic, decision analysis, control theory, expert systems and neural networks. Currently, his research is focused on fuzzy logic, soft computing, computing with words, and the newly developed computational theory of perceptions and precisiated natural language. An alumnus of the University of Tehran, MIT, and Columbia University, Dr. Zadeh is a fellow of the IEEE, AAAS, ACM, AAAI and IFSA, and a member of the National Academy of Engineering. He held NSF Senior Postdoctoral Fellowships in 1956-57 and 1962-63, and was a Guggenheim Foundation Fellow in 1968. Dr. Zadeh was the recipient of the IEEE Education Medal in 1973 and a recipient of the IEEE Centennial Medal in 1984. In 1989, Dr. Zadeh was awarded the Honda Prize by the Honda Foundation, and in 1991 received the Berkeley Citation, University of California.

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In 1992, Dr. Zadeh was awarded the IEEE Richard W. Hamming Medal "For seminal contributions to information science and systems, including the conceptualization of fuzzy sets." He became a Foreign Member of the Russian Academy of Natural Sciences (Computer Sciences and Cybernetics Section) in 1992, and received the Certificate of Commendation for AI Special Contributions Award from the International Foundation for Artificial Intelligence. Also in 1992, he was awarded the Kampe de Feriet Prize and became an Honorary Member of the Austrian Society of Cybernetic Studies. In 1993, Dr. Zadeh received the Rufus Oldenburger Medal from the American Society of Mechanical Engineers "For seminal contributions in system theory, decision analysis, and theory of fuzzy sets and its applications to AI, linguistics, logic, expert systems and neural networks." He was also awarded the Grigore Moisil Prize for Fundamental Researches, and the Premier Best Paper Award by the Second International Conference on Fuzzy Theory and Technology. In 1995, Dr. Zadeh was awarded the IEEE Medal of Honor "For pioneering development of fuzzy logic and its many diverse applications." In 1996, Dr. Zadeh was awarded the Okawa Prize "For outstanding contribution to information science through the development of fuzzy logic and its applications." In 1997, Dr. Zadeh was awarded the B. Bolzano Medal by the Academy of Sciences of the Czech Republic "For outstanding achievements in fuzzy mathematics." He also received the J.P. Wohl Career Achievement Award of the IEEE Systems, Science and Cybernetics Society. He served as a Lee Kuan Yew Distinguished Visitor, lecturing at the National University of Singapore and the Nanyang Technological University in Singapore, and as the Gulbenkian Foundation Visiting Professor at the New University of Lisbon in Portugal. In 1998, Dr. Zadeh was awarded the Edward Feigenbaum Medal by the International Society for Intelligent Systems, and the Richard E. Bellman Control Heritage Award by the American Council on Automatic Control. In addition, he received the Information Science Award from the Association for Intelligent Machinery and the SOFT Scientific Contribution Memorial Award from the Society for Fuzzy Theory in Japan. In 1999, he was elected to membership in Berkeley Fellows and received the Certificate of Merit from IFSA (International Fuzzy Systems Association). In 2000, he received the IEEE Millennium Medal; the IEEE Pioneer Award in Fuzzy Systems; the ASPIH 2000 Lifetime Distinguished Achievement Award; and the ACIDCA 2000 Award for the paper, "From Computing with Numbers to Computing with Words—From Manipulation of Measurements to Manipulation of Perceptions." In addition, he received the Chaos Award from the Center of Hyperincursion and Anticipation in Ordered Systems for his outstanding scientific work on foundations of fuzzy logic, soft computing, computing with words and the computational theory of perceptions. In 2001, Dr. Zadeh received the ACM 2000 Allen Newell Award for seminal contributions to AI through his development of fuzzy logic. In addition, he received a Special Award from the Committee for Automation and Robotics of the Polish Academy of Sciences for his significant contributions to systems and information science, development of fuzzy sets theory, fuzzy logic control, possibility theory, soft computing, computing with words and computational theory of perceptions. In 2003, Dr. Zadeh was elected as a foreign member of the Finnish Academy of Sciences, and received the Norbert Wiener Award of the IEEE Society of Systems, Man and Cybernetics “For pioneering contributions to the development of system theory, fuzzy logic and soft computing.” In 2004, Dr. Zadeh was awarded Civitate Honoris Causa by Budapest Tech (BT) Polytechnical Institution, Budapest, Hungary. Also in 2004, he was awarded the V. Kaufmann Prize by the International Association for Fuzzy-Set Management and Economy (SIGEF). In 2005, Dr. Zadeh was elected as a foreign member of the Polish Academy of Sciences, Korea Academy of Science & Technology and Bulgarian Academy of Sciences. He was also awarded the Nicolaus Copernicus Medal of the Polish Academy of Sciences and the J. Keith Brimacombe IPMM Award. In 2006, he was elected as a foreign member of the National Academy of Sciences of Azerbaijan and was awarded the Pioneer Award for Outstanding Contributions to Soft Computing, Georgia State University, Atlanta, Georgia and the Silicon Valley Engineering Hall of Fame. In 2007, he was awarded the Egleston Medal, Columbia University, New York and became a member of the International Academy of Systems Studies (IASS). In 2009, he was awarded the Franklin Institute Medal, Philadelphia. In 2011, he was awarded the Medal of the Foundation by the Trust of the Foundation for the Advancement of Soft Computing, Spain, the High State Award ‘Friendship Order’, from the President of the Republic of Azerbaijan and the Transdisciplinary Award and Medal of the Society for Design and Process Sciences, Korea. Dr. Zadeh is a recipient of twenty-four honorary doctorates. Dr. Zadeh has single-authored over two hundred papers and serves on the editorial boards of over seventy journals. He is a member of the Advisory Committee, Center for Education and Research in Fuzzy Systems and Artificial Intelligence, Iasi, Romania; Senior Advisory Board, International Institute for General Systems Studies; the Board of Governors, International Neural Networks Society; and is the Honorary President of the Biomedical Fuzzy Systems Association of Japan and the Spanish Association for Fuzzy Logic and Technologies. In addition, he is a member of the Advisory Board of the National Institute of Informatics, Tokyo; a member of the Governing Board, Knowledge Systems Institute, Skokie, IL; and an honorary member of the Academic Council of NAISO-IAAC.

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Issues in Multi-Criteria Decision Making

Ronald R. Yager

Machine Intelligence Institute Iona College

New Rochelle, NY USA

Abstract: Multi-Criteria decision-making is a pervasive problem appearing in many technological domains. During this presentation we shall discuss some issue related to this task. One issue is on the evaluation of multi-criteria decision functions in the face of uncertain information. We shall look at different methods for formulating multi-criteria decision functions to enable the modeling of sophisticated complex relationships between the criteria.

Ronald R. Yager is Director of the Machine Intelligence Institute and Professor of Information Systems at Iona College. He is editor and chief of the International Journal of Intelligent Systems. He has published over 500 papers and fifteen books in areas related to fuzzy sets, human behavioral modeling, decision-making under uncertainty and the fusion of information. He is among the world’s top 1% most highly cited researchers with over 27000 citations. He was the recipient of the IEEE Computational Intelligence Society Pioneer award in Fuzzy Systems. He received the special honorary medal of the 50-th Anniversary of the Polish Academy of Sciences. He received the Lifetime Outstanding Achievement Award from International the Fuzzy Systems Association. He received an honorary doctorate degree, honoris causa, from the State University of Information Technologies, Sofia Bulgaria. Dr. Yager is a fellow of the

IEEE, the New York Academy of Sciences and the Fuzzy Systems Association. He has served at the National Science Foundation as program director in the Information Sciences program. He was a NASA/Stanford visiting fellow and a research associate at the University of California, Berkeley. He has been a lecturer at NATO Advanced Study Institutes. He is a visiting distinguished scientist at King Saud University, Riyadh Saudi Arabia. He is a distinguished honorary professor at the Aalborg University Denmark. He received his undergraduate degree from the City College of New York and his Ph. D. from the Polytechnic University of New York.

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Soft Computing: Philosophical, Mathematical, and Theoretical Foundations

of Cognitive Robotics and Computational Intelligence

Yingxu Wang

Schulich School of Engineering University of Calgary

2500 University Dr. NW Calgary, Alberta, Canada, T2N 1N4

Abstract The 2016 World Conference on Soft Computing is dedicated to Prof. Lotfi A. Zadeh’s seminal work on fuzzy sets, fuzzy logic, and fuzzy inference methodologies for 50 years as well as his 95th birthday. Dr. Zadeh is one of the greatest minds in contemporary philosophy, mathematics, computer science, intelligence science, and engineering applications. In his vision, “Soft computing is a consortium of methodologies which play an important role in the conception, design and utilization of intelligent systems.” He has identified that “The principal methodologies in soft computing are: fuzzy logic, neurocomputing, evolutionary computing, cyber computing, probability computing, and machine learning.” This keynote lecture attempts to highlight Dr. Zadeh’s philosophical, mathematical, and theoretical thoughts on soft computing. It demonstrates that soft computing is an indispensable methodology to the emerging fields of cognitive computing and cognitive robotics in cognitive informatics and computational intelligence. Latest advances in the framework of denotational mathematics inspired by Dr. Zadeh such as fuzzy truth algebra, fuzzy probability theory, fuzzy concept algebra, fuzzy semantic algebra, and fuzzy inference algebra [Wang, 2000-2016], as well as applications in soft computing are briefly presented. This talk also intends to express that the key principle we learnt from Dr. Zadeh is that a proven theory of soft computing may lead to a systematic solution to a wide range of real-world problems, so as Immanuel Kant (1724-1804) asserted: “There is nothing more practical than a good theory.”

Yingxu Wang is professor of cognitive informatics, brain science, software science, and denotational mathematics. He is President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic/). He is a Fellow of ICIC, a Fellow of WIF (UK), a P.Eng of Canada, and a Senior Member of IEEE and ACM. He is/was visiting professor (on sabbatical leave) at Oxford University (1995), Stanford University (2008 | 2016), UC Berkeley (2008), and MIT (2012), respectively. He received a PhD in Computer Science from the Nottingham Trent University in 1998 and has been a full professor science 1994. He is the founder and steering committee chair of the annual IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chief of Int’l Journal of Cognitive Informatics & Natural Intelligence, founding Editor-in-Chief of Int’l Journal

of Software Science & Computational Intelligence, Associate Editor of IEEE Trans. on SMC - Systems, Editor-in-Chief of Journal of Advanced Mathematics & Applications, and Editor-in-Chief of Journal of Mathematical & Computational Methods. Dr. Wang is the initiator of a few cutting-edge research fields such as cognitive informatics, denotational mathematics (concept algebra, process algebra, system

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algebra, semantic algebra, inference algebra, big data algebra, fuzzy truth algebra, fuzzy probability algebra, fuzzy semantic algebra, visual semantic algebra, and granular algebra), abstract intelligence (αI), the neural circuit theory, mathematical models of the brain, cognitive computing, cognitive learning engines, cognitive knowledge base theory, and basic studies across contemporary disciplines of intelligence science, robotics, knowledge science, computer science, information science, brain science, system science, software science, data science, neuroinformatics, cognitive linguistics, and computational intelligence. He has published 400+ peer reviewed papers and 29 books in aforementioned transdisciplinary fields. He has presented 30 invited keynote speeches in international conferences. He has served as general chairs or program chairs for more than 20 international conferences. He is the recipient of dozens international awards on academic leadership, outstanding contributions, best papers, and teaching in the last three decades. He is one of the top 2.5% scholars worldwide according to the big data system of Research Gate international stats. president of the International Fuzzy Systems Association.

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Perspectives on Type-2 fuzzy Sets and Systems

Jerry M. Mendel

Department of Electrical Engineering Hughes Aircraft Electrical Engineering Building

3740 McClintock Ave. Los Angeles, CA 90089-2564, USA

Abstract This talk will provide some interesting and novel perspectives about type-2 fuzzy sets and systems. It will also explain what to me are some of the “game-changing” technical events that have occurred in the type-2 field during the past 16+ years, and will describe future directions and challenges for the type-2 field.

Jerry M. Mendel received the Ph.D. degree in electrical engineering from the Polytechnic Institute of Brooklyn, Brooklyn, NY. Currently he is Professor of Electrical Engineering at the University of Southern California in Los Angeles, where he has been since 1974. He has published over 570 technical papers and is author and/or co-author of 12 books, including Uncertain Rule-based Fuzzy Logic Systems: Introduction and New Directions (Prentice-Hall, 2001), Perceptual Computing: Aiding People in Making Subjective Judgments (Wiley & IEEE Press, 2010), and Introduction to Type-2 Fuzzy Logic Control: Theory and Application (Wiley & IEEE Press, 2014). He is a Life Fellow of the IEEE, a Distinguished Member of the IEEE Control Systems Society, and a Fellow of the International Fuzzy Systems Association. He was President of the IEEE Control Systems Society in 1986, a member of the Administrative Committee of the IEEE Computational Intelligence Society for nine years, and Chairman of its Fuzzy Systems Technical Committee and the Computing With Words Task Force of that TC. Among his awards are the 1983 Best Transactions Paper Award of the IEEE Geoscience and

Remote Sensing Society, the 1992 Signal Processing Society Paper Award, the 2002 and 2014 Transactions on Fuzzy Systems Outstanding Paper Awards, a 1984 IEEE Centennial Medal, an IEEE Third Millenium Medal, and a Fuzzy Systems Pioneer Award (2008) from the IEEE Computational Intelligence Society.

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Systems Intelligence in Healthcare – Changes in Lifestyle Behavior and Vitals

Hiroshi Nakajima

Omron Corporation Horikawa Higashiiru

Shiokoji-Dori, Shimogyo-Ku, Kyoto, 600-8530, Japan

Abstract Due to the arrival of super aging society, the lifestyle and chronic diseases such as hypertension and diabetes have been making serious impacts on social problems in all over the world. Besides prevention and treatment of the diseases, healthcare improvement is also the center of important concerns by happiness in life. According to the social trends with the technology developments of wearable devices and ICT, data centric knowledge extraction and evidence discovery based on systems approach would play an important role in healthcare science and technology. In this talk, the idea of Systems Intelligence will be conceptually introduced. The digital healthcare system and data analysis results accumulated by the system will follow the ideas of the systems approach in healthcare. The results showed the behavioral and vital changes according to seasons and weeks and they would be the valuable information and knowledge in healthcare.

Hiroshi Nakajima received the B.Eng. degree in System Engineering from Kobe University, Japan, in 1985, and Ph.D. degree in Systems Information Science from Kumamoto University, Japan, in 2004. He is currently Chief Specialist of Technology at Omron Corporation. Besides long term career at industry, he also has some academic careers such as visiting professor at Kyushu Institute of Technology. He has focused on developing the general solution for improvement of health in humans, artifacts such as machines and information, and energy consumptions by applying sensory inspection and soft computing. He received the best paper award from Interaction’99 in 1999, the best author award from Information Processing Society of Japan in 2000, the Industrial Outstanding Application Award from International Fuzzy Systems Association in 2007, the best paper award from Japan Society for Fuzzy Theory and Intelligent Informatics in 2009, and Biomedical Wellness Award from SPIE in 2011.

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Decomposable Graphical Models: On Learning, Fusion and Revision

Rudolf Kruse

Fakultät für Informatik Building 29, Room 008

Otto-von-Guericke-Universität Magdeburg Universitätsplatz 2

D-39106 Magdeburg, Germany

Abstract Decomposable Graphical Models are of high relevance for complex industrial applications. The Markov network approach is one of their most prominent representatives and an important tool to structure uncertain knowledge about high dimensional domains. But also relational and possibilistic decompositions turn out to be useful to make reasoning in such domains feasible. Compared to conditioning the decomposable model on given evidence, the learning of the structure of the model from data as well as the fusion of several decomposable models is much more complicated. The important belief change operation revision has been almost entirely disregarded in the past, although the problem of inconsistencies is of utmost relevance for real world applications. In this talk these problems are addressed by presenting a successful complex application in an automotive industry.

Rudolf Kruse is Professor at the Otto-von-Guericke University of Magdeburg (Germany), where he is leading the Computational Intelligence Group. His current research interests include data science and intelligent systems. His group is successful in various industrial applications in cooperation with companies such as Volkswagen, Daimler, SAP, and British Telecom. He obtained his Ph.D. and his Habilitation in Mathematics from the Technical University of Braunschweig in 1980 and 1984 respectively. Following a stay at the Fraunhofer Gesellschaft, he joined the Technical University of Braunschweig as a professor of computer science in 1986. Since 1996 he is a full professor at the Department of Computer Science of the Otto-Von-Guericke University of Magdeburg in Germany. Rudolf Kruse has coauthored 15 monographs and 25 books as well as more Than 350 refereed technical papers in various scientific areas. He is a Fellow of the International Fuzzy Systems Association (IFSA), Fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI) and Fellow of the Institute of Electrical and Electronics Engineers (IEEE).

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Fuzzy and cognitive approaches of similarities

Bernadette Bouchon-Meunier

LIP6, Université Pierre et Marie Curie BC 169, 4 place Jussieu

75252 Paris Cedex 05, France

Abstract Fuzzy logic provides interesting tools for data mining and decision making, mainly because of its ability to represent imperfect information, for instance by means of imprecise categories, measures of resemblance or aggregation methods. This ability is of crucial importance when databases are complex, large, and contain heterogeneous, imprecise, vague, uncertain, incomplete data. We focus our study on the use of similarities which are key concepts for all attempts to construct human-like automated systems or assistants to human task solving since they are very natural in the human process of categorization underlying many natural capabilities such as language understanding, pattern recognition or decision-making. We base our discourse on cognitive approaches of similarities, stemming for instance from Tversky's and Rosch's seminal works, among others. We point out several types of measures of comparison compatible with these cognitive foundations, including measures of similarity and dissimilarity. We show that they can be involved in many steps of the process of data mining, such as clustering, construction of prototypes, fuzzy querying, for instance. We eventually illustrate our discourse by examples of similarities used in real-world problems.

Bernadette Bouchon-Meunier is a director of research emeritus at the National Centre for Scientific Research, the former head of the department of Databases and Machine Learning in the Computer Science Laboratory of the University Pierre et Marie Curie-Paris 6 (LIP6). She is the Editor-in-Chief of the International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, the (co)-editor of 25 books, and the (co)-author of five. She has (co-)authored more than 400 papers on approximate and similarity-based reasoning, as well as the application of fuzzy logic and machine learning techniques to decision-making, data mining, risk forecasting, information retrieval, user modelling, sensorial and emotional information processing. Co-executive director of the IPMU International Conference held every other year since 1986, she also served as the FUZZ-IEEE 2010 and FUZZ-IEEE 2013 Program Chair, the IEEE Symposium Series on Computational Intelligence (SSCI 2011) General Chair and the FUZZ-IEEE 2012 Conference Chair, as well as the Honorary chair of IEEE SSCI 2013 and IEEE CIVEMSA 2013. She is currently the IEEE Computational Intelligence Society Vice-

President for Conferences, the IEEE France Section Vice-President for Chapters and the IEEE France Section Computational Intelligence chapter chair. She is an IEEE fellow and an International Fuzzy Systems Association fellow. She received the IEEE Computational Intelligence Society Meritorious Service Award in 2012.

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Recognition Technology: Lotfi’s look to the future

from the late 1990s

Jim Keller

Electrical & Computer Engineering University of Missouri

307 Engineering Building West Columbia, MO 65211, USA

Abstract In 1998, Lotfi Zadeh coined the term Recognition Technology, saying that it refers to current or future systems that have the potential to provide a "quantum jump in the capabilities of today’s recognition systems". Recognition Technology will include systems that incorporate three advances: new sensors, novel signal processing and soft computing. That vision has come to pass. I will discuss these three aspects of recognition technology through two quite different case studies that I am involved in: landmine detection and eldercare technology. They are both recognition systems. The former has a goal of detecting objects, explosive hazards, to help save lives while the latter focuses on recognizing human activities to allow older adults to live independently with a higher quality of life. While the sensors applied to these problems are dissimilar, they share many of the signal processing and pattern recognition approaches.

James M. Keller received the Ph.D. in Mathematics in 1978. He holds the University of Missouri Curators’ Professorship in the Electrical and Computer Engineering and Computer Science Departments on the Columbia campus. He is also the R. L. Tatum Professor in the College of Engineering. His research interests center on computational intelligence: fuzzy set theory and fuzzy logic, neural networks, and evolutionary computation with a focus on problems in computer vision, pattern recognition, and information fusion including bioinformatics, spatial reasoning in robotics, geospatial intelligence, sensor and information analysis in technology for eldercare, and landmine detection. His industrial and government funding sources include the Electronics and Space Corporation, Union Electric, Geo-Centers, National Science Foundation, the Administration on Aging, The National Institutes of Health, NASA/JSC, the Air Force Office of Scientific Research, the Army Research Office, the Office of Naval Research, the National Geospatial Intelligence Agency, the Leonard Wood Institute, and the Army Night Vision and Electronic Sensors Directorate. Professor Keller has coauthored over 400 technical

publications. Jim is a Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the International Fuzzy Systems Association (IFSA), and a past President of the North American Fuzzy Information Processing Society (NAFIPS). He received the 2007 Fuzzy Systems Pioneer Award and the 2010 Meritorious Service Award from the IEEE Computational Intelligence Society. He finished a full six year term as Editor-in-Chief of the IEEE Transactions on Fuzzy Systems, followed by being the Vice President for Publications of the IEEE Computational Intelligence Society from 2005-2008, and has been an elected CIS Adcom member. He is the IEEE TAB Transactions Chair and a member of the IEEE Publication Review and Advisory Committee. Among many conference duties over the years, Jim was the general chair of the 1991 NAFIPS Workshop and the 2003 IEEE International Conference on Fuzzy Systems.

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From Fuzzy Sets to Spatial Cognition

Christian Freksa

Universität Bremen P.O. Box 330 440

28334 Bremen, Germany

Abstract Perception and cognition are resource-limited processes. They generate coarse information about environments that can be analyzed and described at arbitrary levels of resolution and abstraction. Fuzzy set theory and possibility theory provide a conceptual framework to characterize the relation between coarse information and high-precision ‘ground truth’ in environments and in mental states. This relation – a mapping between coarse and fine entities – can be used in two ways: to infer high-precision information from coarse descriptions or to generate coarse descriptions from precise data. The mappings are particularly useful for interfacing high-resolution technical systems with human-friendly low-resolution systems such as natural language. In the interaction between cognitive agents such as humans and robots, we are confronted with a third mapping: the mapping between two coarse systems that do not have access to a common high-resolution ground truth. From a theoretical perspective, such a coarse-to-coarse mapping can be viewed as a composition of a (fictitious) coarse-to-fine mapping composed with a fine-to-coarse mapping. However, the composition does not yield a useful model for the actual mechanisms that enable cognitive agents to successfully interact. In my talk I will describe how fuzzy sets and possibility theory serve as a framework for concepts in spatial cognition that permit natural interaction between cognitive agents in spatial environments.

Christian Freksa is Professor of Cognitive Systems at the Faculty of Mathematics and Informatics at the University of Bremen, Germany. He directs the Bremen Spatial Cognition Center. His research concerns representation and reasoning with incomplete, imprecise, lean, coarse, approximate, fuzzy, and conflicting knowledge about physical environments. Particular emphasis is on qualitative spatial and temporal reasoning. Freksa received a PhD in Artificial Intelligence from UC Berkeley. He carried out research at the Max Planck Institute and at the Technical University of Munich, at the International Computer Science Institute in Berkeley, and at the University of Hamburg. From 1996 to 2014 he directed national research initiatives on Spatial Cognition supported by the German Research Foundation (DFG). Freksa is a Fellow of the European AI society ECCAI.

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Fuzzy preferences and majority in multiagent decision making: from status quo to innovative

decisions

Janusz Kacprzyk

Intelligent Systems Laboratory Systems Research Institute, Polish Academy of Sciences

Newelska 6, 01-447 Warsaw, Poland Abstract: Our main concern is the process of multiagent decision making under fuzzy preferences and fuzzy majority. We have a set of options and a set of agents, human beings or not, who present their testimonies assumed to be fuzzy preference relations. We look for an option (or a set of options) which is best acceptable by the group of agents, i.e. by a fuzzy majority (e.g. most) of them. We deal with relatively small sets of options and agents. The fuzzy majority, introduced by Kacprzyk (1985), is represented by a fuzzy linguistic quantifier like “most”, “almost all”, “much more than a half”, etc. dealt with by, e.g., Zadeh’s calculus of linguistically quantified propositions or Yager’s OWA operators. Then, from the fuzzy preferences of the individual agents we determine some solution concept like Kacprzyk’s fuzzy Q-core, i.e. a fuzzy set of options which are not defeated in pairwise comparisons by the required fuzzy majority Q (e.g. most) of agents. This solution concept can then be extended by taking into account the importance of agents and relevance of options. First, we follow the usual path in this area, i.e. we claim that a “better” group decision can be found if agents are at consensus. We perform a consensus reaching session, find consensual fuzzy preferences, and determine a fuzzy set of agent whose fuzzy preferences are close to the consensual ones; this implies what we call status quo solutions. Then, taking another point if departure, related to some claims of knowledge and innovation management, we find another fuzzy set of agents whose preferences are far from the consensual ones; this implies what we call innovative solutions. We show, as a possible way to obtain those status quo and innovative solutions, new augmented fuzzy Q-cores for those consensory and dissensory agents, and analyze the solutions obtained from the point of view of their novelty and innovativeness which are measured by using some numerical indexes. We show some example of choosing a regional development policy.

Janusz Kacprzyk graduated from the Department of Electronic, Warsaw University of Technology in Warsaw, Poland with M.Sc. in automatic control, his Ph.D. in systems analysis and D.Sc. (“habilitation”) in computer science from the Polish Academy of Sciences. He is Professor of Computer Science at the Systems Research Institute, Polish Academy of Sciences, Professor of Computerized Management Systems at WIT – Warsaw School of Information Technology, and Professor of Automatic Control at PIAP – Industrial Institute of Automation and Measurements, in Warsaw, Poland, and Department of Electrical and Computer Engineering, Cracow University of Technology, in Cracow, Poland. He is Honorary Foreign Professor at the Department of Mathematics, Yli Normal University, Xinjiang, China, and Visiting Scientist at the RIKEN Brain Research Institute in Tokyo, Japan. He is Full Member of the

Polish Academy of Sciences and Foreign Member of the Spanish Royal Academy of Economic and Financial Sciences (RACEF). He is Fellow of IEEE and of IFSA.

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He was a frequent visiting professor in the USA, Italy, UK, Mexico and China. His main research interests include the use of computational intelligence, notably fuzzy logic, in decisions, optimization, control, data analysis and data mining, with applications in databases, ICT, mobile robotics, etc. He is the author of 5 books, (co)editor of 60 volumes, (co)author of ca. 400 papers. He is the editor in chief of 5 book series at Springer, and of 2 journals, and a member of editorial boards of more than 40 journals. He is a member of Award Committee of IEEE CIS, a member of Adcom (Administrative Committee) of IEEE CIS, and a Distinguished Lecturer of IEEE CIS. He received many awards, notably: The 2006 IEEE CIS Pioneer Award in Fuzzy Systems, The 2006 Sixth Kaufmann Prize and Gold Medal for pioneering works on soft computing in economics and management, and The 2007 Pioneer Award of the Silicon Valley Section of IEEE CIS for contribution in granular computing and computing in words, and Award of the 2010 Polish Neural Network Society for exceptional contributions to the Polish computational intelligence community. Currently he is President of the Polish Society for Operational and Systems Research and Past President of IFSA (International Fuzzy Systems Association).

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Fuzzy Logic Can Justify and Improve Semi-Heuristic Data and Image Processing Techniques:

Main Idea and Case Studies

Vladik Kreinovich

Department of Computer Science University of Texas at El Paso

500 W. University El Paso, TX 79968, USA

Abstract: Fuzzy logic techniques were originally designed to translate expert knowledge -- which is often formulated by using imprecise ("fuzzy") from natural language (like "small") -- into precise computer-understandable models and control strategies. Such a translation is still the main use of fuzzy techniques. For example, we want to control a complex plant for which no good control technique is known, but for which there are experts how can control this plant reasonably well. So, we elicit rules from the experts, and then we use fuzzy techniques to translate these rules into a control strategy. Lately, it turned out that fuzzy techniques can help in another class of applied problems: namely, in situations when there are semi-heuristic techniques for solving the corresponding problems, i.e., techniques for which there is no convincing theoretical justification. Because of the lack of a theoretical justification, users are reluctant to use these techniques, since their previous empirical success does not guarantee that these techniques will work well on new problems. Also, these techniques are usually not perfect, and without an underlying theory, it is not clear how to improve their performance. For example, linear models can be viewed as first approximation to Taylor series, so a natural next approximation is to use quadratic models. However, e.g., for l^p-models, when they do not work well, it is not immediately clear what is a reasonable next approximation. In this talk, we show that in many such situations, the desired theoretical justification can be obtained if, in addition to known (crisp) requirements on the desired solution, we also take into account requirements formulated by experts in natural-language terms. Naturally, we use fuzzy techniques to translate these imprecise requirements into precise terms. To make the resulting justification convincing, we need to make sure that this justification works not only for one specific choice of fuzzy techniques (i.e., membership function, "and"- and "or"-operations, etc.), but for all combinations of such techniques which are consistent with the corresponding practical problem. As examples, we provide the detailed justification of: 1) sparsity techniques in data and image processing -- a very successful hot-topic technique whose success is often largely a mystery; 2) l^p-regularization techniques in solving inverse problems -- an empirically successful alternative to Tikhonov regularization appropriate for situations when the desired signal or image is not smooth; and 3) non-linear empirical models of soil mechanics used in road construction. Several other applications will be mentioned.

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Vladik Kreinovich received his MS in Mathematics and Computer Science from St. Petersburg University, Russia, in 1974, and PhD from the Institute of Mathematics, Soviet Academy of Sciences, Novosibirsk, in 1979. From 1975 to 1980, he worked with the Soviet Academy of Sciences; during this time, he worked with the Special Astrophysical Observatory (focusing on the representation and processing of uncertainty in radioastronomy). For most of the 1980s, he worked on error estimation and intelligent information processing for the National Institute for Electrical Measuring Instruments, Russia. In 1989, he was a visiting scholar at Stanford University. Since 1990, he has worked in the Department of Computer Science at the University of Texas at El Paso. In addition, he has served as an invited professor in Paris (University of Paris VI), France; Hong Kong; St. Petersburg, Russia; and Brazil. His main interests are the representation and processing of uncertainty, especially interval computations and intelligent control. He has published six books, eleven edited books, and more than 1,100 papers. Vladik is a member of the editorial board of the international journal "Reliable

Computing" (formerly "Interval Computations") and several other journals. In addition, he is the co-maintainer of the international Web site on interval computations http://www.cs.utep.edu/interval-comp . Vladik is Vice President for Publications of IEEE Systems, Man, and Cybernetics Society; he served as President of the North American Fuzzy Information Processing Society 2012-14; is a foreign member of the Russian Academy of Metrological Sciences; was the recipient of the 2003 El Paso Energy Foundation Faculty Achievement Award for Research awarded by the University of Texas at El Paso; and was a co-recipient of the 2005 Star Award from the University of Texas System.

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Fuzzy Logic and Non-Statistical Association Measures

Ildar Batyrshin

Center for Computing Research of Mexican National Polytechnic Institute (CIC IPN)

Eje Central Lázaro Cárdenas Norte 152 Col. San Bartolo Atepehuacan, Mexico, D.F.

C.P. 07730, Mexico Abstract The idea of measuring of positive and negative associations (or correlations) between data is very popular in data analysis. The Pearson’s correlation coefficient as a measure of association is used in many approaches to data analysis, machine learning, signal processing etc. This correlation coefficient serves as a prototype for construction of association measures in different application areas. This talk will discuss the general methods of construction of association measures as functions satisfying the properties of Pearson’s correlation coefficient. These methods use the technique developed in the theory of fuzzy logic and aggregation functions. Examples of association and correlation measures constructed by these methods on different domains are discussed. The measures of associations and correlations on [0,1], on the set of fuzzy set, on the set of time series etc. are considered.

Ildar Batyrshin graduated from the Moscow Physical-Technical Institute, Faculty of Control and Applied Mathematics in 1975. He received his PhD from the Moscow Power Engineering Institute in 1983 and Dr. Sc. (habilitation) from the Higher Attestation Committee of Russian Federation in 1996. He joined the Department of Informatics and Applied Mathematics of Kazan State Technological University, Kazan, Russia in 1975, and served as the Department Head in 1997-2003. Since 1999, he was also a leading researcher of the Institute of Problems of Informatics of Academy of Sciences of the Republic of Tatarstan, Russia. He joined the Research Program of Applied Mathematics and Computations of Mexican Petroleum Institute in 2003 as a leading researcher. Since 2014 he is with the Center for Computing Research of Mexican National Polytechnic Institute (CIC IPN) as a Titular Professor C. He is a Past President of Russian Association for Fuzzy Systems and Soft Computing (RAFSSoftCom), a member of the Council of Mexican Society for Artificial Intelligence, a member of the Board of Directors of NAFIPS, Senior Member of IEEE Computational Intelligence Society, a member of

editorial boards of several scientific journals. His awards: Research Level 2 of the National System of Researchers of Mexico; Best Research Prize of Mexican Petroleum Institute in 2007 for the Development of Fuzzy Expert System in Water Production Diagnosis; Honorary Professor of Obudu University, Budapest, Hungary; Honorary Researcher of the Republic of Tatarstan, Russia; State Research Fellowship of the Presidium of Russian Academy of Sciences for Distinguished Researchers (1997-2003). He served as a Co-Chair of 9 International Conferences on Soft Computing, Artificial Intelligence and Computational Intelligence. He is a co-author and co-editor of 19 books and special volumes of journals. He is an author of more than 200 scientific publications.

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Explorations in Ordinal Preference Theory with the Savage’s Omelet Problem

Michio Sugeno

Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku

Tokyo, 152-8550, Japan

Abstract There are two preference models used in preference theory for multi-criteria decision making: cardinal models with addition-multiplication on real numbers and ordinal models with max-min operations on ordinal numbers. In this study, we explore ordinal preference models based on various S-integrals which are counterparts of various Choquet integrals used as cardinal preference models. We examine a family of S-integrals such as S-integrals, Symmetric S-integrals, Cumulative Prospect Theory S-integrals, Bi-Capacity S-integrals and Level-Dependent S-integrals through the Savage’s Omelet Problem which has been often used as a simple illustrative example in multi-criteria decision making. In this problem, however, we find many preference orders of acts depending on the consequents of acts. In the examinations, we find that there exist some preference orders which cannot be modeled even by Bi-Capacity S-integrals and Level-Dependent S-integrals. In order to completely solve the problem, we successfully apply a novel modeling scheme called Hierarchical S-integrals. Finally, reviewing the history of cardinal preference models, we introduce an essential concept of ‘admissibility’ into preference theory. With this concept, we can clearly state the primary objective of preference theory. Considering it, we pose a hypothesis that any admissible preference orders could be modeled with our Hierarchical S-integrals in the case of ordinal preference or Hierarchical Choquet integrals in the case of cardinal preference.

Michio Sugeno was born in Yokohama; Japan in 1940. After graduating from the Department of Physics, the University of Tokyo, he worked at a company for three years. Then, he served the Tokyo Institute of Technology as Research Associate, Associate Professor and Professor from 1965 to 2000. After retiring from the Tokyo Institute of Technology, he worked as Laboratory Head at the Brain Science Institute, RIKEN from 2000 to 2005, as Distinguished Visiting Professor at Doshisha University from 2005 to 2010 and then as Emeritus Researcher at the European Centre for Soft Computing, Spain from 2010 to 2015. He is Emeritus Professor at the Tokyo Institute of Technology. He was President of the Japan Society for Fuzzy Theory and Systems from 1991 to 1993, and also President of the International Fuzzy Systems Association from 1997 to 1999. He is the first recipient of the IEEE Pioneer Award in Fuzzy Systems with Zadeh in 2000. He also received the 2010 IEEE Frank Rosenblatt Award and Kampét de Feriét Award in 2012. His research interests are Choquet calculus, fuzzy measure theory, nonlinear control, preference theory, applications of Systemic Functional

Linguistics and language functions of the brain.

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Venue

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INTERNATIONAL HOUSE UC BERKELEY 2299 Piedmont Ave, Berkeley

California 94720

http://ihouse.berkeley.edu/ The International House, Berkeley is a multi-cultural residence and program center serving students at the University of California, Berkeley. According to the International House, its mission is to foster intercultural respect, understanding, lifelong friendships and leadership skills for the promotion of a more tolerant and peaceful world (Wikipedia). The conference will take place in classic Spanish/Moorish-inspired event rooms of the House.

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