CS 188: Artificial Intelligence (Fall 2011, UC Berkeley): Lecture 09

CS 188: Artificial Intelligence

CS 188: Artificial Intelligence (Fall 2011, UC Berkeley). Instructor: Professor Dan Klein. This course introduces the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm. Topics include heuristic search, problem solving, game playing, knowledge representation, logical inference, planning, reasoning under uncertainty, expert systems, learning, perception, language understanding.

Lecture 09 - Markov Decision Processes (cont.)

Go to the Course Home or watch other lectures:

Lecture 01 - Introduction

Lecture 02 - Queue-Based Search

Lecture 03 - A* Search and Heuristics

Lecture 04 - Constraint Satisfaction Problems

Lecture 05 - Constraint Satisfaction Problems (cont.)

Lecture 06 - Adversarial Search: Game Trees, Minimax

Lecture 07 - Expectimax Search

Lecture 08 - Utilities, Markov Decision Processes

Lecture 09 - Markov Decision Processes (cont.)

Lecture 10 - Reinforcement Learning