Spring 2022 - CMPT 310 E100
Artificial Intelligence Survey (3)
Class Number: 6071
Delivery Method: In Person
Provides a unified discussion of the fundamental approaches to the problems in artificial intelligence. The topics considered are: representational typology and search methods; game playing, heuristic programming; pattern recognition and classification; theorem-proving; question-answering systems; natural language understanding; computer vision. Students with credit for CMPT 410 may not take this course for further credit.
Artificial Intelligence (AI) is the part of computer science concerned with systems that learn, reason and make/support decisions. The goal of this course is to provide students with a survey of different aspects of artificial intelligence. A variety of approaches with general applicability will be developed. The first topic is searching for solutions to complex decision and planning problems (search strategies and heuristics). Symbolic logic will be presented as a formalism for representing knowledge in AI systems. Probability as a mechanism for handling uncertainty in AI will be presented, with a focus on Bayesian networks. We will introduce basic concepts of machine learning, including as decision trees and neural nets.
- Game playing
- Reasoning under uncertainty (probability)
- Bayesian networks
- Machine learning
To be discussed the first week of classes
MATERIALS + SUPPLIES:
Artificial Intelligence: Foundations of Computational Agents, David L. Poole and Alan Mackworth, New York : Cambridge University Press, 2010, 9780521519007
Artificial Intelligence (6th Edition). Structures and Strategies for Complex Problem Solving, George Luger, Addison Wesley, 2009, 9780321545893
Artificial Intelligence: A Modern Approach (3rd Edition), Stuart J. Russell, Peter Norvig, Prentice Hall, 2010
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TEACHING AT SFU IN SPRING 2022
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