Artificial Intelligence

John Ross

Yuki Yabushita

Sharon Pieloch

Steven Smith

8 Types of AI Robotics

Fuzzy Logic

Expert Systems

Intelligent Agents

Natural Language Processing

Artificial Vision

Neural Networks

Genetic Algorithms

Expert Systems “An Expert System is a system that employs human

knowledge captured in a computer to solve problems that ordinarily require human expertise”.

In the early 1960’s, the General-purpose Problem Solver was introduced (GPS). This machine helped solve some basic problems.

Source: (www.usfca.edu).

Geologic Expert System Model Part 1

Source: www.odyssey.maine.edu

Geologic Expert System Model Part 2

Source: www.odyssey.maine.edu

Geologic Expert System Model Part 3

Source: www.odyssey.maine.edu

Source: www.growinglifestyle.com

Over the past 10 years, expert systems have replaced human workers in fields such as industrial, science and research, and even for recreational purposes such as mowing your lawn. ES’s will eventually be able to solve complex solutions such as the traveler who wants the fastest route for 10 cities.

The Future of Expert Systems

The i-Mow from Toro

Natural Language Processing

NLP has become very popular over the last decade. Speech recognition can make work a bit easier if implemented in the right places. One of the drawbacks has been the difference in languages and syllables. Computers must be trained to adapt to individual voice patterns which takes time. “It is clear that for applications that are eye-busy, hand-busy, a trainer that incorporates NLP technology is very useful” (www.cs.duke.edu).

                                                          

      

Fig. 1: Examples of typical documents used: a) Chinese, b) English, c) Greek, d) Korean, e) Malayalam, f) Persian, g)

Russian.

Natural Language Processing: The Multiple Languages Barrier

Source: www.bmva.ac.uk

Breaking the Language Barrier

To incorporate ES units that can be translated in most common languages.

To bypass syllable irregularities between different languages (such as Japanese characters that use two symbols).

NLP systems that can comprehend the intended use of certain words. Fuzzy logic can give computers protocols of how certain words are used in certain cultures.

Integrating Global NLPOne future challenge is to create cells

(nodes) that will comprehend all major languages.

In the future, robots will recognize multiple voice patterns in multiple languages.

Genetic Algorithms

Use simulated populat ion of “art if icial life” to solve complex problems

Reach opt imal solut ion faster than other methods

May create solut ion humans never thought of

Genetic Algorithms Design “chromosome” which is a problem

solut ion

Randomly generate a populat ion

Test for f itness & select the best

“Reproduce” using the best

Start over with the new populat ion

http://cs.felk.cvut.cz/~xobitko/ga/

Applicat ions of GA

Genetic programming—computers write their own code Robotic ants collect food Bots playing soccer game

www.lalena.com

Elect rical circuit design Students required two

weeks, GA designed in 30 minutes

University of Idaho

Intelligent Agents

Software programs that: Sense their environment

Act independently

Can interact with other agents (including humans)

Intelligent Agents

Examples: Web search agents

(web crawlers)

Web server maintenance bots

Personal assistants

Chatter bots (talking agents)

www.agentland.com

Intelligent Agents

Future uses for agents: Network maintenance

Agent-oriented programming

Mobile, physical agents (intelligent robots)

Fuzzy logic

Similar processes to those of neural networks.

It is designed with specific formulas or rules.

Gives a clear output by having a calculation.

Usually used for “fuzzy” things (unclear estimations).

Fuzzy logic

General idea/rules If service is poor, good, excellent..? If food is rancid, or delicious..?We can combine these two categories to

to one list. If service is poor or the food is

rancid..? If service is excellent or food is

delicious…?

The MathWorks, http://www.mathworks.com/access/helpdesk/help/toolbox/fuzzy/fuzzy.shtml

Fuzzy logic

Neural Network Inputs: all facts Hidden layer: finding

the possible ways to predict

Outputs: final decision of prediction

Neural Network

Different paradigm for computing.Operates similar to our human brain.Takes inputted data, and predict some

actions based on these data.Learns new ways of solving by adding

some more facts.

Neural Network

Business ApplicationFinance; credit risk decision support,

predicting bad debtors, preventing application fraud

Marketing; customer attrition, analyzing consumer-spending patterns

Forecasting sea surface temperature

Fuzzy logic

Business ApplicationCruise control for carPDASubway systemPrediction system for early recognition

of earthquakesAir conditioning system

www.ai.mit.edu

Robotics• Definition: A

programmable, self controlled device consisting of electronic, electrical, or mechanical units

• It is a machine that functions in place of a living agent

History of Robotics

Joseph Engelberger & George Devol were the first to develop a commercially successful robot known as Unimate

Unimate was an assembly line arm used to extract die castings and perform spot welding on auto body assembly lines

Began industrial robot revolution by selling to General Motors in 1962

Advantages of Robotics

Perform highly repetitive tasks more efficiently and accurately

Ability to perform tasks that would otherwise be considered dangerous

Improved management control

Greater productivity

Higher quality

Can reduce costs of manufactured goods

Give countries an economic advantage on the world market.

Current Applications

Exploration Space

Ocean

Volcanoes

Military/Police Destroy/Locate

bombs

Espionage

Medical Operations

Productions of medicines

Development of prosthetic (bionic) limbs

Artificial Vision

The ability of a machine to see its environment, to make choices about its action based on what it sees and to recognize visual input according to general patterns.

Range of Applications

Production line quality control

Video surveillance

Self driving motor

vehicles