Introduction, Problem Representation, Search, Knowledge Representation and Reasoning, AI Programming, Neural Networks, Knowledge Discovery, Distributed Intelligence and Agents, Turing Test and the Ontology of Intelligence, Cellular Automata, Learning.

Semester:

January

Rationale:

Artificial intelligence (AI) is the branch of computer science that is concerned with the automation of intelligent behavior. This course provides a comprehensive exposure to the paradigms and techniques necessary for study and research in artificial intelligence. Emphasis is placed on the historical evolution and the emerging trends in technology

Catalog Description:

Introduction, Problem Representation, Search, Knowledge Representation and Reasoning, AI Programming, Neural Networks, Knowledge Discovery, Distributed Intelligence and Agents, Turing Test and the Ontology of Intelligence, Cellular Automata, Learning.

Credits:

3(3-0)

Prerequisite:

Consent of the Instructor

Course Outline:

Introduction

1. Definition of AI, Historical Development of AI
2. Applications of AI
3. AI Techniques

Problem Representation

1. State-Space Representation
2. Problem-Reduction Representation

Search

1. Blind and Non-Blind Searches
2. Heuristic Search
3. Best-First Search
4. Optimal Search

Knowledge Representation and Reasoning

1. Predicate Calculus
2. Frame Representation
3. Semantic Networks
4. Ontology of Knowledge Representation
5. Fuzzy Representation

AI Programming

1. Lisp
2. Prolog
3. Web-Programming

Neural Networks

1. Back Propagation
2. Self-Organization
3. Applications

Knowledge Discovery, Distributed Intelligence and Agents

Turing Test and the Ontology of Intelligence

Cellular Automata

1. Qualitative treatment of reproducing automata
2. Artificial life
3. Application

Learning

Textbook:

Lecture Notes

Reference Books:

S.J. Russell and P. Norvig (1995):

Artificial Intelligence, A Modern Approach, Prentice Hall

N.J. Nilsson (1998):

Artificial Intelligence, A New Synthesis, Morgan Kaufmann

S. Wolfram (2002):

A New Kind of Science, Wolfram Media, Inc.Journals and Magazines:

AI Magazine

Artificial IntelligenceIEEE Transactions on System, Man and CyberneticsInternational Journal of Intelligent SystemsInternational Journal of Man-Machine StudiesWeb Link http://www.cs.ait.ac.th/~sada

Grading System:

The final grade will be computed from the following constituent parts: mid-semester exam (40%), final exam (40%) and assignments/projects (20%). Closed-book examination is used for both mid-semester and final exam.

Instructor:

Prof. R. Sadananda

Contact us: Olivier Nicole

Last update: Jul 2003