Computing Science 551
Artificial Intelligence: Representation and Reasoning
Second Term, 1997-98
Time: TR 11-12:20
Place: GSB 511
Intructor: Russ Greiner
Purpose:
This course provides a graduate-level introduction to artificial intelligence,
with an emphasis on the design on agents that
act intelligently -- ie, that "do the right thing" in complex environments,
by acting optimally given the limited information and computational resources
available. We will focus on agents that can reason (eg, answer queries,
or produce plans) from their stored knowledge, using logic-based and/or
probability-based techniques as appropriate; and can learn (acquire
new information) from their observations and experiences.
Prerequisite: CMPUT 451 or equivalent. Students who are interested
in the material but do not have the required prerequisite are encouraged
to talk to the instructor.
Textbooks:
Course Outline: With a focus on "AI as design of rational
agents", topics will include
-
search-based agents : uninformed search, heuristic search,
constraint satisfaction local search, stochastic search(GSAT)
-
logical agents: "Wumpus world", building/using
logical knowledge bases, planning
-
decision-theoretical agents: probability, belief nets, influence
diagrams, Markov decision process, dynamic belief/decision networks
-
learning agents: foundations (PAC-learning/Bayesian learning), learning
decision trees/neural nets/belief nets, reinforcement learning
Lecture
Notes
Evaluation:
Late Policy: No late assignments or papers will be accepted.
Office Hours:
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