'Expectimax search' presentation slideshows

CS 188: Artificial Intelligence Fall 2008

330 views • 32 slides

CSE 473: Artificial Intelligence Spring 2012

CSE 473: Artificial Intelligence Spring 2012. Adversarial Search: Expectimax Dan Weld. Based on slides from Dan Klein, Stuart Russell, Andrew Moore and Luke Zettlemoyer. 1. Space of Search Strategies. Blind Search DFS, BFS, IDS Informed Search Systematic: Uniform cost, greedy, A*, IDA*

469 views • 31 slides

CS 188: Artificial Intelligence Fall 2007

447 views • 31 slides

Advanced Artificial Intelligence

506 views • 29 slides

Lecture 1C: Adversarial Search(Game)

312 views • 29 slides

Lirong Xia

Utilities and decision theory. Lirong Xia. Friday, Feb 28, 2014. Reminder. Midterm Mar 7 in-class open book and lecture notes simple calculators are allowed cannot use smartphone/laptops/ wifi practice exams and solutions (check piazza) Project 2 deadline Mar 18 midnight.

455 views • 28 slides

Lirong Xia

277 views • 27 slides

CS 5368: Artificial Intelligence Fall 2010

CS 5368: Artificial Intelligence Fall 2010. Lecture 6: Expectimax Search 9/14/2010. Mohan Sridharan Slides adapted from Dan Klein. Recap: Adversarial Games. Deterministic, zero-sum games: Tic-tac-toe, chess, checkers. One player maximizes result. The other minimizes result.

392 views • 24 slides

Markov Decision Processes

Markov Decision Processes. Stochastic, sequential environments. Game show. A series of questions with increasing level of difficulty and increasing payoff Decision: at each step, take your earnings and quit, or go for the next question If you answer wrong, you lose everything. $100 question.

376 views • 20 slides

Temporal Difference Learning with Expectimax Search for the CGI-Threes

404 views • 16 slides

Temporal Difference Learning with Expectimax Search for the Threes-bot

411 views • 16 slides