Academics / Courses / DescriptionsCOMP_SCI 348: Intro to Artificial Intelligence
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Prerequisites
Students must have taken [CS 111 and (CS 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. Stat 304 is *not* a substitute for Comp_Sci 214.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: Mohammed A. Alam or Prof. Birnbaum or Prof. Edith Elkind
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