Catalog Description: Ideas and techniques underlying the design of intelligent computer systems. Topics include search, game playing, knowledge representation, inference, planning, reasoning under uncertainty, machine learning, robotics, perception, and language understanding.

Units: 4

Prerequisites: COMPSCI 61A, COMPSCI 61B, and COMPSCI 70.

Formats:
Summer: 6.0-6.0 hours of lecture and 2.0-3.0 hours of discussion per week
Fall: 3.0-3.0 hours of lecture and 1.0-1.5 hours of discussion per week
Spring: 3.0-3.0 hours of lecture and 1.0-1.5 hours of discussion per week

Grading basis: letter

Final exam status: Written final exam conducted during the scheduled final exam period

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Class Schedule (Fall 2024):
CS 188 – TuTh 15:30-16:59, Dwinelle 155 – Igor Mordatch, Pieter Abbeel

Class Schedule (Spring 2025):
CS 188 – TuTh 12:30-13:59, Dwinelle 155 – John F Canny, Oliver Grillmeyer

Class homepage on inst.eecs

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Department Notes:

Course objectives: An introduction to the full range of topics studied in artificial intelligence, with emphasis on the "core competences" of intelligent systems - problem solving, reasoning, decision making, and learning - and on the logical and probabilistic foundations of these activities.

Topics covered:

• history
• intelligent agents
• uninformed search
• informed search
• constraint satisfaction
• game-playing
• logical agents
• propositional logic
• first-order logic
• inference in first-order logic
• resolution, logic programming
• planning, plan execution
• uncertainty, probability theory, probabilistic inference
• Bayesian networks and associated inference algorithms
• optimal decisions under uncertainty
• optimal sequential decisions, Markov decision processes
• learning agents
• inductive learning, decision trees
• neural networks
• Bayesian learning
• natural language processing
• perception/vision
• robotics
• philosophical foundations

Related Areas:

• Artificial Intelligence (AI)