• Course outline
• A free version of Common Lisp can be obtained from Franz.

Lecture nodes

• Lecture 1
• Lecture 2
• Lecture 3
• Lecture 4
• Lecture 5
• Lecture 6
• Lecture 7
• Lecture 8
• Lecture 9
• Lecture 10
• Lecture 11
• Lecture 12
• Lecture 13
• Lecture 14
• Lecture 15
• Lecture 16

Lisp code

• Student data base example
• Missionaries and cannibals example with depth-first search
• Missionaries and cannibals example with breadth-first search
• A simple breadth-first search example
• A simple depth-first search example
• A simple best-first search example
• A simple hill-climbing search example
• Search using association lists for representing data
• Search using structures for representing data
• Iterative breadth-first search example
• Beam search example
• 5-puzzle with number of tiles in proper places as heuristic for informed search, and 8-puzzle version of it
• A genetic algorithm
• A forward chaining algorithm
• A backward chaining algorithm
• Wang's algorithm

Assignments and announcements

• Introductory readings:
  • What is AI? (by John McCarthy).
  • History and Promise of AI (by David Waltz).
  • The Human Intelligence Enterprise. Why I am Optimist (by Patrick Winston).
• Homework 1.
• Homework 2. !!! NEW DEADLINE -- MARCH 18, 2003. !!!
• Manhattan distance heuristic (promissed help for the 5-puzzle problem).
• !!! Test 1 !!!
• Homework 3.
• Homework 4: Create a knowledge base with 30 - 40 rules in a domain of your choice, and use forward or backward chaining code from the section above to implement a simple KBS. Submit the description of your system, the code (hardcopy) and a disk. Deadline: May 6, 2002.
• !!! Test 2 !!!
• Final exam questions.

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