B351/Q351: Introduction to Artificial Intelligence and Computer Simulation

Spring 1997



Course Content

The purpose of this course is to introduce students to important methods and models in artificial intelligence and to computer simulation in cognitive science.

The course is organized around the following topics:

  • Heuristic search
  • Representation and reasoning: predicate logic, frames, production systems, resolution theorem proving
  • Learning: connectionist models, symbolic learning
  • Perception and understanding: vision, speech, natural language processing
  • Action and evolution: planning, robotics; genetic algorithms

Each topic will be discussed in the abstract and in terms of its relation to AI and cognitive science in general, but the focus will be on algorithms and their implementation. For each topic, there will be a programming assignment; programs will be written in Scheme. For most assignments, some of the code will be provided.

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Email to everyone

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Schedule and Lecture Notes

All lecture notes appear here. By 8:00 am on the morning of a lecture, you can access a reasonably final version of the notes for that day, but the notes may be updated later.

Overview of AI and Scheme Review


Representation and Reasoning

Learning and Connectionism


Perception and Understanding

Evolution and Action

Overview of Other Topics

Final exam (due on Tuesday, 6 May, 23:59)

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Homework guidelines


  1. Homework 1
  2. Homework 2
  3. Homework 3
  4. Homework 4
  5. Homework 5


  1. Homework 1: 8s puzzle and map coloring
  2. Homework 2: production system
  3. Homework 3: hopfield network (also requires matrix routines and vector utilities)
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Other Web Sites of Interest

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To the IU Bloomington Home Page. To the IU Cognitive Science Home Page.

Last updated: 1 May 1997
URL: http://www.indiana.edu/~gasser/Q351/home.html
Comments: gasser@cs.indiana.edu
Copyright 1997, The Trustees of Indiana University