B351/Q351: Introduction to Artificial Intelligence and Computer Simulation
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.
- Mike Gasser
- Who I am
- Office hours: M 10:30-12, Tu 3-4:30;
Lindley 230H, 855-7078
You may drop by any time during my office hours, but I prefer you
an appointment so you won't overlap with somebody else.
Please do not come to my office unannounced outside my office hours.
If we can't find a time during my regular office hours, I'll arrange
another time to meet.
- Kyle Wagner
- Who I am
- Office hours: M 1-4 Lindley 330i,
If you can't make my office hours, email me or call me to make
an appointment. If I happen to be in my office at other times
and I'm not busily working on something, I'll be happy to talk
with you. Please feel free to email me
(firstname.lastname@example.org) or call me at home (337-1322)
between 10am and 10pm (I sleep at other times).
- Discussion section
- Where and when:W, 6:50-7:40, SW218
- Purpose: to ask Kyle about the assignments, the
lecture material, or other related topics that he may or may not
know anything about. It's not required; it's only for your benefit.
- Programming assignments (75%)
There are 5 programming assignments.
You may collaborate on homework if you make it clear to us that
you are doing so.
Consult the Computer
Science Department Statement on Academic Integrity if you are
unsure about what is ethical.
If you are still unsure, ask us.
- Final exam (25%)
This will be an in-class, open-book, open-notes exam covering
the content of the entire course.
Emphasis will be on material not directly related to the assignments.
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
- Week 1 (13-17 Jan)
- Reading: R&K, ch. 1
- Assignment 1
- Week 2 (20-24 Jan)
- Reading: R&K, ch. 2, 3
- Week 3 (27-31 Jan)
Representation and Reasoning
- Assignment 2
- Week 4 (3-7 Feb)
- Reading: R&K, ch. 4, 5
- Week 5 (10-14 Feb)
- Reading: R&K, ch. 6
- Week 6 (17-21 Feb)
- Reading: R&K, ch. 9, 10
Learning and Connectionism
- Assignment 3
- Week 7 (24-28 Feb)
- Reading: R&K, ch. 18
- Week 8 (3-7 Mar)
- Reading: R&K, ch. 17
- Week 9 (10-14 Mar)
Perception and Understanding
- Assignment 4
- Week 11 (31 Mar-4 Apr)
- Reading: R&K, ch. 14
- Week 12 (7-11 Apr)
- Reading: R&K, ch. 15, 21.2
- Week 13 (14-18 Apr)
- Reading: R&K, ch. 21.3-4
Evolution and Action
- Assignment 5
- Week 14 (21-25 Apr)
Overview of Other Topics
Final exam (due on Tuesday, 6 May, 23:59)
- Homework 1
- Homework 2
- Homework 3
- Homework 4
- Homework 5
- Homework 1: 8s puzzle and
- Homework 2: production system
- Homework 3: hopfield network
Last updated: 1 May 1997
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