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Class Schedule

The class schedule is a guide to topics that will be discussed and when they will be discussed on a weekly basis. The week begins on a Tuesday before the co-curricular days and on a Thursday after the co-curricular days.

All slide sets are files. To save paper and ink, I suggest you do not print slides too far in advance and not before the course begins as changes may be made.

Week 1: September 9 & 11

Readings: Chapter 1 Introduction to Prolog, Chapter 2 Syntax and Meaning of Prolog Programs, Chapter 3.1, 3.2 Representation and oprations on lists, & Chapter 8.1 .. 8.4 On programing style and technique
Slides:

• Administrvia Not worth printing, just for introductory class, contains pointers to the on-line information.
• Prolog introduction
• List utility predicates

Week 2: September 16 & 18

Readings: Chapter 3.3 Operator notation, Chapter 3.4 Arithmetic, Chapter 4.1 Finding a Path in a Graph, & Chapter 6.2 Constructing and decomposing compound terms.
Slides:

• Prolog examples
• Highlights of pattern matching
• Diagram for the maze example
• Defining operators − prefix unary, postfix unary and infix binary

Week 3: September 23 (Report 1 due) & 25

Readings: Chapter 5 Controlling Backtracking, Chapter 6 Builtin Predicates, & Chapter 7 Constraint Logic Programming.
Slides:

• Cut and not − efficent execution
• Constraint logic programming

Week 4: September 30 & October 2

Readings: Chapters 8.5 Improving Efficency (difference lists, holes and accumulators), & Chapter 9 Operations on Data Structures
Slides:

• Accumulators − using stacks and queues to gather results
• Diagrams for the binary tree example

Week 5: October 7 (Report 2 due) & 9

Readings: Chapter 25.8 Simple theorem proving
       Chapter 23 Language Processing with Grammar Rules
Slides:

• Resolution method & theorem proving − the mathematical basis of Prolog

Week 6: October 14 (Class exam 1) & 16

Readings: Chapter 23
Slides:

• Chat program − using natural language to communicate with a program
• Grammars − the mathematical basis of grammars, design and progrmming.

Week 7: October 21 & October 23

Readings: Chapter 11 Basic searchs: depth first, breadth first, iterative deeping, bidirectional
Slides:

• Basic search methods.

Week 8: October 28 (Report 3 due) & November 4 (Class exam 2)

Readings: Chapter 12 Heuristic search and the A* algorithm.
Slides:

• Heuristic search methods
• A* algorithm

Week 9: November 6 & 11

Readings: Chapter 13 Best-first search minimizing time & space
Slides:

• RTA* algorithm
• IDA* algorithm
• RBFS algorithm

Week 10: November 13 & 18 (Report 4 due)

Readings: Chapter 15 Knowledge representation and expert systems.
Slides:

• Expert systems.

Week 11: November 20 & 25

Readings: Chapter 16 Probabilistic networks with Bayesian reaasoning.
Slides:

• Bayseian networks Why have them. What are they
• Bayseian networks: Defining probability equations

Week 12: November 27 & December 4 (Report 5 due)

Readings: Chapter 16 Probabilistic networks with Bayesian reaasoning.
Slides:

• Bayseian networks: Evidence nodes. d-separation & d-connection. Benefits & drawbacks
• d-separation example
• Bayseian networks: Model structure

Subject to change