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COMP_SCI 348: Intro to Artificial Intelligence

Quarter Offered

Fall : 12:30-1:50 TuTh ; Hammond
None : 11-11:50 MWF ; Alam
Spring : 9:30-10:50 TuTh ; Rubenstein
Summer : 9:30-10:50 TuTh (Sync: Class meets remotely) ; Alam

Prerequisites

Students must have taken [EECS 111 and (EECS 214 or be a CogSci major)] or be a Computer Science Masters or PhD student, or obtain instructor permission, in order to register for this course.

Description

Core techniques and applications of artificial intelligence. Representation retrieving and application of knowledge for problem solving, planning, probabilistic inference, and natural language understanding.

  • This course satisfies the AI Breadth Requirement.

OPTIONAL TEXTBOOK: Russell & Norvig , Artificial Intelligence: A Modern Approach , Prentice Hall, 3rd edition

COURSE INSTRUCTOR: Prof. Kristian Hammond (Fall), Mohammed A. Alam (Winter & Summer) & Prof. Rubenstein (Spring)
COURSE COORDINATOR: Prof. Kristian Hammond

COURSE GOALS: The goal of this course is to expose students to the basic ideas, challenges, techniques, and problems in artificial intelligence. Topics include strong (knowledge-based) and weak (search-based) methods for problem solving and inference, and alternative models of knowledge and learning, including symbolic, statistical and neural networks.

DETAILED COURSE TOPICS:

  • Philosophical foundations of artificial intelligence
  • Intelligent agents
  • Search, including A*, iterative deepening
  • Logical formalisms, propositional and first order predicate calculus
  • Planning, from STRIPS to Partial Order Planning
  • Probability & uncertainty, including Bayesian inference and Bayes networks
  • Machine learning, including decision trees, neural nets, hill climbing, genetic algorithms

COURSE OBJECTIVES: After this course, students should be able to

  • Articulate key problems, both technical and philosophical, in the development of artificial intelligence
  • Teach themselves more about AI through reading texts and research articles in the field
  • Apply AI techniques in the development of problem-solving and learning systems