'Highest minimax value' diaporamas de présentation

CSE 573 : Artificial Intelligence Autumn 2012

CSE 573 : Artificial Intelligence Autumn 2012. Adversarial Search Dan Weld. Based on slides from Dan Klein, Stuart Russell, Andrew Moore and Luke Zettlemoyer. 1. In class. Printed out a/b example tree (should have printed alpha beta algo on reverse side

598 views • 46 slides

Agents and environments

Agents and environments. Environment types. Fully observable (vs. partially observable): An agent's sensors give it access to the complete state of the environment at each point in time .

501 views • 43 slides

Adversarial Search

1.07k views • 32 slides

Game and Tree Searching

Game and Tree Searching . Learning Objectives. Introduction to games Optimal decisions in games Alpha-Beta pruning Real-time decisions. Introduction to Games. Games as Search Problems Frameworks: two-player, multi-player; zero-sum; perfect information Minimax algorithm Perfect decisions

468 views • 31 slides

Turn-Based Games

510 views • 29 slides

Adversarial Search

280 views • 21 slides

Games & Adversarial Search

428 views • 18 slides

Adversarial Search

437 views • 15 slides