Artificial Intelligence

M.C. Juan Carlos Olivares Rojas

Course Syllabusjolivares@uvaq.edu.mx

January, 2009

Outline• Introduction

• Topics

• Grading

• Recommendations

• References

IntroductionThe students will know in detailed form the construction and working of intelligent systems

The students will programming and knows diferent kind of languages and applications for artificial intelligence

Basic Concepts1.1 Basic Concepts

1.2 Applications

1.3 The Intelligent Systems and Learning

1.4 Semantic Networks

1.5 Match and Description Method

1.6 Analogy Problem

1.7 Abstraction Recognition

1.8 Knowledge Interpretation

Networks and Basic Search2.1 Blind Methods

2.2 Heuristic Method

2.3 The Best Path

2.4 Redundant Paths

2.5 Trees and Search with Adversary Algorithmic Methods

2.6 Trees and Search with Adversay Heuristic Methods

Logic3.1 Knowledge Representation

3.2 Preposition Logic

3.3 Predicate Logic

3.4 Automatic Deduction

Rules and Chained Rules4.1 Deduction Systems

4.2 Reaction Systems

4.3 Progressive and Regressive Chained

4.4 Cognitive Modeling

4.5 Problem Solving Models

Lisp Programming5.1 Introduction5.2 Structures5.3 Basic Operations5.4 Control Structure5.5 Mathematic Operations5.6 Predicate Function5.7 Relations and Sets5.8 Input and Outputs5.9 Implementation5.10 Backup and Recovery

Grading• Only two partial and one Final Exams (only the last partial).

• 70% Partial Exam• 30% Homeworks and Practices• 10% Quizzes

Recommendations• The classes begin at 19 to 21 hours at 6C Classroom on Tuesday and at Electronic Lab on Thursday

• The advisory should be by E-mail, Instant Messenger or by another electronics media

• E-mail: jolivares@iuvaq.mx• MSN: juancarlosolivares@hotmail.com• Skype: juancarlosolivares• Web:http://dsc.itmorelia.edu.mx/jcolivares

Recommendations• The homework must be delivery in Classroom or before class throught moodle or by CD.

• The rubric of work contains:– Cover– Abstract– Introducction– Development*– Conclusions– References**

ReferencesNilsson, N. (2001). Artificial Intelligence. A New Synthesis. McGraw-Hill.

Russel, S. and Norving, P. (2004). Artificial Intelligece. A New Approach. Pearson Prentice Hall.

Winston, P. (1998). Artificial Intelligence. 3rd. Ed., Adisson-Wesley.

ReferencesKnight, R. (1997). Artificial Intelligence. 2nd Ed. McGraw-Hill.

Tanimoto, S. (1998). The Elements of Artifical Intelligence using Common LISP . W. H. Freeman Company.

Questions?