data-driven agent-based social simulation of moral values evolution samer hassan universidad...
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Data-Driven Agent-Based Social Simulation of Moral Values Evolution
Samer Hassan
Universidad Complutense de Madrid
University of Surrey
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Objective
Study the evolution of Spanish society in the period 1980-2000
Data-Driven Agent-Based Modelling
Applying several Artificial Intelligence techniques
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The Problem
Aim: simulate the process of change in moral values in a period in a society
Plenty of factors involved
Nowadays, centred in the inertia of generational change: To which extent the demographic dynamics
explain the mentality change?
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The Problem
Input Data loaded: EVS-1980 Quantitative periodical info Representative sample of Spain Allows Validation
Intra-generational: Agent characteristics remain constant Macro aggregation evolves
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Design of Mentat
Agent: EVS Agent MS attributes
Life cycle patterns
Demographic micro-evolution: • Couples• Reproduction• Inheritance
World: 3000 agents
Grid 100x100
Demographic model
Network: Communication with
Moore Neighbourhood
Friends network
Family network
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Friendship Network
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Friendship Network
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Friendship Network
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Friendship Network
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Friendship Network
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Friendship Network
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Friendship Network
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Friendship Network
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Methodological aspects
Data-driven ABM Microsimulation concepts
Design with qualitative info Life cycle, micro-processes
Introduction of empirical equations Life expectancy, birth rate, different probabilities
Initialisation with survey data
Validation with different empirical data
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Mentat in action
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Results
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Results
It may arise new sociological knowledge:
Demographic Dynamics are a key factor for the prediction of social trends in Spanish society
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Introduction of AI: Fuzzy Logic
Why Fuzzy Logic? Social sciences are characterized by uncertain and vague
knowledge Different concept than probability
0.6
0.4
0.2
0.1
0
Old
10.150
10.240
10.530
0.80.820
0110
AdultYoungAge
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Fuzzification
Attributes
Similarity
Friendship & its evolution
Couples
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Introduction of AI: NLP
Fuzzy logic helps for ABM qualitative input
NLP helps for ABM qualitative output
Experimenting with life-events generation: Output in natural language: life-story of a representative
individual (Ex: hyper-inflation)
Applications: NL format makes direct comparison with real stories possible Information very simple for any individual to understand Complementing explanations of quantitative research
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Quantitative & Qualitative Output Generation
Life-Story of Representative Individual (ideal
type)
Analysis , Filtering and NLG
Macro Trends
Micro processes : interactions
Quantitative Statistics and
Graphs
European Values Survey
Simple Filtering
Content Determination :
Complex filtering based
on rules
Discourse Planning :
Ordering for a coherent story
Surface Realization :
Natural Language Generation
Events log
(XML)
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An example: part of the XML output
<Log Id="i49"> <Description /> <Attribute Id="name" Value="rosa" /> <Attribute Id="last_name" Value="pérez" /> <Attribute Id="sex" Value="female" /> <Attribute Id="ideology" Value="left" /> <Attribute Id="education" Value="high" />
... <Events> <Event Id="e1" Time="1955" Action="birth" Param="" /> <Event Id="e2" Time="1960" Action="friend" Param="i344" /> <Event Id="e3" Time="1960" Action="friend" Param="i439" /> <Event Id="e4" Time="1961" Action="friend" Param="i151" /> <Event Id="e5" Time="1962" Action="horrible" Param="childhood" /> <Event Id="e6" Time="1963" Action="best friend" Param="i151" /> <Event Id="e7" Time="1964" Action="believe" Param="god" /> <Event Id="e8" Time="1964" Action="every week go" Param="church" />
... <Event Id="e16" Time="1968" Action="problems" Param="drugs" /> <Event Id="e17" Time="1971" Action="grow" Param="adult" /> <Event Id="e18" Time="1971" Action="friend" Param="i98" /> <Event Id="e19" Time="1972" Action="involved" Param="labour union" /> <Event Id="e20" Time="1972" Action="friend" Param="i156" /> <Event Id="e21" Time="1973" Action="get" Param="arrested" /> <Event Id="e22" Time="1973" Action="learn" Param="play guitar" /> <Event Id="e23" Time="1975" Action="became" Param="hippy" />
... <Event Id="e36" Time="1985" Action="divorce" Param="i439" /> <Event Id="e37" Time="1987" Action="couple" Param="i102" /> <Event Id="e38" Time="1987" Action="live together" Param="i102" /> <Event Id="e39" Time="1987" Action="have" Param="abortion" />
...</Log><Log Id="i50"> <Description /> <Attribute Id="name" Value=“francisco" />
...
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An example: part of the life-story generated
Rosa Pérez was born in 1955, and she met Luis Martínez, and she met Miguel López. She suffered a horrible childhood, and she had a very good friend: María Valdés, and she believed in God, and she used to go to church every week. . . .
When she was a teenager, (...) she had problems with drugs, and she became an adult, and she met Marci Boyle, and while she was involved in a labour union, she met Carla González and she got arrested. She learned how to play the guitar, and so she became a hippy, getting involved in a NGO.. . .
She met Sara Hernández, and she stopped going to church, and she met Marcos Torres, and she fell in love, desperately, with Marcos Torres, but in the end she went out with Miguel López, and she co-habitated with Miguel López, and she had a child: Melvin López.. . .
She met Sergio Ruiz, and she separated from Miguel López, and she went out with Sergio Ruiz, and she co-habitated with Sergio Ruiz. She had a abortion, and so she had a depression, and she had a crisis of values. She was unfaithful to Sergio Ruiz with another man.. . .
Nowadays she is an atheist.
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Contents
The Problem
ABM Mentat: Design
ABM Mentat: Results
AI: Fuzzy Logic
AI: Natural Language Processing
AI: Data Mining
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Introduction of AI: Data Mining
Data Mining is the process of extracting patterns and relevant information from large amounts of data
Design: Allows simplification, locates redundant attributes
Pre-processing of empirical data (surveys): Clustering: selection of qualitative “ideal types”
Post-processing of simulation output: Clustering:
• Shows non-visible patterns • Comparison of patterns• Different life-stories for each pattern
Classification: evolution of “ideal types”
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Limitations & Future Work
Enough demography! Overcome methodological limitation: implementing
diffusion of moral values
Quest for a proper cognitive model for this task ...or forget about it definitely not BDI
Improve other aspects: ABM design (Ex: friendship ties may weaken) Fuzzy inference Quality of biographies
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Contents License
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Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/
You are free to copy, modify and distribute it as long as the original work and author are cited
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