ECS 170 - AI

Course Outline

General Advise: Please read all the reading assignments. You learn a number of things that I cannot possibly cover. You can skip topics that are NOT listed  AND not covered in the class. You are responsible for everything that is on the Reading List OR that is covered in the class (or both).

Topics to be Covered and Approximate Schedule: (Subject to revision)

• 1. Introduction

        (a) Introduction to AI -Read Chapters 1-2 (1 Lecture)

History.
Central Issues.
      Lecture#1 – History (Notes)  [html]

Lecture#2 – Intro to AI (Notes)  [html]
Glossary of AI terms

       (b)  Introduction to LISP (1 discussion session by TA, No lecture on this topic)
Homework Assignment #0. Focus on formulation, state spaces, and review of LISP

• 2. Problem Solving by Search (4 Lectures)

This topic covers three important categories in Searching: Blind Search, Heuristic Search, Adversarial Search
Read Chapter 3. Sections 3.1 thru 3.6 (skip bidirectional search), Section 3.8
Read Chapter 4. Sections 4.1, 4.2 and 4.5

• How to write a LISP program for Depth First Search?
• Search Slides – Notation [ppt]
• Blind Search Slides [ppt]
• Lecture #3 notes [html]
• Heuristic Search Slides  [pdf]
• Programming Assignment # 1. (Focus is on using LISP and solve a Search Problem) (3 weeks time)
• Homework Assignment #1. Focus on search methods
• Adversarial search [ppt] [pdf]

Read Chapter 5, Sections 5.1 thru 5.4 and 5.8

• 3. Knowledge Representation  (4 lectures)

This part covers the very broad area of what knowledge is and some of the numerous methods of solving logic problems. The main methods covered are Propositional Logic (very quick survey), First Order Predicate Logic and Rule based systems.
Knowledge Representation and Logic [html]
Propositional logic [pdf]
Read Chapter 6.
Predicate or First Order Logic- [pdf]
Validity and inference, models and entailment, rules of inference, Resolution
Read Chapter 7.1 thru 7.5. (skip 7.6 thru 7.9)
Read Chapter 9. Sections 9.1 thru 9.3; 9.5 thru 9.8
Homework Assignment #2. Focus on Logic

Midterm. 6 February (Tentative, but most likely)

• 4. Learning

Decision tree learning. ID3, C4.5
Read Chapter 18.1 thru 18.5
Homework Assignment #3 Focus on Decision Trees

Learning in neural networks Perceptrons and error back propagation in feed forward networks
Read Chapter 19
Programming Assignment #2. Focus on Learning

• 5. Probabilistic Reasoning and Decision Making

Read Chapters 14, 15 and 16
Basic probability concepts, conditional probability. Baye's Theorem
Joint probability distributions.

Naïve Bayes

More on Bayes Nets and Belief networks.
Homework Assignment #4. Focus on probabilistic reasoning

• 6. Planning? (Not likely)

Planning slides (ppt)

• 7. Summary

Final Examination (covers the entire course)

Department of Computer Science
University of California at Davis
Davis, CA 95616-8562

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Page last modified on 12/27/2002