CISC 352/3.0 Artificial Intelligence
Original author: Jim Rodger
Last Revised: October 16, 2006
An introduction to the basic principles and tools of artificial intelligence. Problem solving methods and knowledge representation techniques.
Prerequisites: CISC 235/3.0, 260/3.0.
Artificial Intelligence (AI) has existed as a recognizably distinct field of study
for about five decades. Historically, AI emphasized reasoning
and thought processes and fidelity to human models. More recent work
has shifted the focus to include the actions that artificial systems perform,
and the application of an ideal standard of rationality to that behaviour.
This first course in Artificial Intelligence provides students an
introduction to the field, presenting some of the major ideas that have
emerged from the roughly past half century of AI research.
The courses to which this course is a prerequisite are:
- CISC-452/3.0 (Neural and Genetic Computing)
- CISC-453/3.0 (Topics in Artificial Intelligence)
- CISC-471/3.0 (Computational Biology)
- COGS-300/3.0 (Programming Cognitive Models)
- COGS-400/3.0 (Neural and Genetic Computing)
This course is required in BMCO and COGS.
history; foundations and contributing disciplines; the Intelligent-Agent theme;
agent design hierarchy; the state of the art
- Problem Solving
searching; uninformed search strategies; avoiding repeated states; informed
search; heuristic functions; local search and optimization; constraint
satisfaction problems; variable and value ordering; adversarial search and
games; minimax; alpha-beta pruning; state of the art
- Knowledge and Reasoning
logical agents and propositional logic; reasoning and effective inference;
first order logic; assertions and queries in FOL; knowledge engineering;
knowledge representation; categories and objects; actions, situations and
events; mental events, objects, beliefs; reasoning with categories; reasoning
with default information; truth maintenance
- Perception (Computer Vision)
image formation; early processing and edge detection; extracting
three-dimensional information (shape from x); object recognition and pose
estimation; vision for navigation
planning problems; state-space search; partial order planning; planning graphs;
planning and propositional logic (as time allows)
- Russell, S. and Norvig, P. Artificial Intelligence A Modern Approach
(2nd Edition), Prentice Hall, 2003.
- Winston, P. H. Artificial Intelligence (3rd Edition), Addison-Wesley, 1992.
- Nilsson, N. Artificial Intelligence A New Synthesis, Morgan Kaufmann, 1998.