For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Cke8v4
Topics: Minimax, expectimax, Evaluation functions, Alpha-beta pruning
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor – Stanford University
http://onlinehub.stanford.edu/
Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
https://profiles.stanford.edu/percy-liang
Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
https://profiles.stanford.edu/dorsa-sadigh
To follow along with the course schedule and syllabus, visit:
https://stanford-cs221.github.io/autumn2019/#schedule
0:00 Introduction
0:43 Course plan
2:09 A simple game
3:29 Roadmap
4:01 Game tree
5:05 Two-player zero-sum games
8:55 Example: chess
11:43 Characteristics of games
22:33 Game evaluation example
29:01 Expectimax example
33:51 Extracting minimax policies
34:21 The halving game
38:44 Face off
45:41 Minimax property 2
48:18 Minimax property 3
53:02 A modified game
53:49 Expectiminimax example
55:26 Expectiminimax recurrence
57:19 Computation
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