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ICS-270A, Intorduction to Artificial Intelligence, Spring 2001
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Course Outline

Course Overview
Topics covered Include: Heuristic search, Adverserial search, Constraint Satisfaction Problems, knowledge representation, propositional and first order logic, inference with logic, Planning, learning and probabilistic reasoning.


Assignments:
There will be weekly homework-assignments, a project, a midterm and/or a final.

Course-Grade:

Homeworks plus project will account for 50% of the grade, midterm and/or final 50% of the grade.

Syllabus:
Subject to changes

Week Topic Date  
Week 1
  • Introduction and overview: What is AI? History
    Nillson Ch.1 (1.1-1.5), RN: chapters 1,2.

  • Problem solving: Statement of Search problems: state space graph, problem types, examples (puzzle problem, n-queen, the road map, travelling sales-man.)
    Nillson Ch 7. RN: chapter 3, Pearl: ch.1
04-02
Week 2
  • Uninformed search: Greedy search, breadth-first, depth-first, iterative deepening, bidirectional search.
    Nillson Ch. 8, RN: Ch. 3, Pearl: 2.1, 2.2

  • Informed heuristic search: Best-First, Uniform cost, A*, Branch and bound.
    Nillson Ch. 9, RN: Ch. 4 , Pearl, 2.3.1
04-09
Week 3
  • Properties of A*, iterative deepening A*, generating heuristics automatically. Learning heuristic functions.
    Nillson Ch. 9, 10.3, RN: chapter 4, Pearl: 3.1, 3.2.1, 4.1, 4.2

  • Game playing: minimax search, alpha-Beta pruning.
    Nillson Ch. 12, RN: Ch. 5.
04-16
Week 4
  • Constraint satisfaction problems
    Definitions, examples, constraint-graph, constraint propagation (arc-consistency, path-consistency), the minimal network.
    Reading: selected papers, class notes.

  • Backtracking and variable-elimination
    advanced search: forward-checking, Dynamic variable orderings, backjumping, solving trees, adaptive-consistency.
    Reading: selected papers, class notes.
04-23
Week 5
  • Knowledge and Reasoning:
    Propositional logic, syntax, semantics, inference rules.
    Nillson Ch. 13, RN: Ch 6.

  • Propositional logic. Inference, First order logic
    Nillson Ch. 14, RN: Ch. 6
04-30
Week 6
  • Knowledge representation:
    First-order (predicate) Logic.
    Nillson Ch. 15, RN: Ch. 9.

 05-07
Week 7
  • Inference in First Order logic
    Nillson Ch. 16, RN: Ch. 9, 10(unification).

  • Planning:
    Logic-based planning, the situation calculus, the frame problem.
    Nillson Ch. 21, RN: Ch. 11.
05-14
Week 8
  • Planning: Planning systems, STRIP, regression planning, current trends in planning: search-based, and propositional-based.
    Nillson Ch. 22, RN: Ch. 11.

  • Reasoning and planning under uncertainty
    Nillson Ch. 19, RN: chapter 14.
05-21
Week 9
  • Memorial Day.

  • Belief networks:
    Inference, acting and learning.
    Nillson Ch. 19, Ch. 20, RN: Ch. 15
05-28
Week 10
  • Assorted topics
06-04



Resources on the Internet
  • AI on the Web: A very comprehensive list of Web resources about AI from the Russell and Norvig textbook.

Essays and Papers