CS 188. Introduction to Artificial Intelligence

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: 4.0

Prerequisites: Computer Science 61A; Computer Science 61B; Computer Science 70.

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

Grading basis: letter

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


Class Schedule (Fall 2018):
TuTh 2:00PM - 3:29PM, Wheeler 150 – Daniel L. Klein, Pieter Abbeel

Class Schedule (Spring 2019):
MoWe 5:00PM - 6:29PM, Wheeler 150 – Sergey Levine, Stuart Russell

Class homepage on inst.eecs

General Catalog listing


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: