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The Turk First chess playing machine, made in 1770.
Computing Machines Begin to appear in 1940's
Claude Shannon Father of Information Theory & Computer Chess
Position Evaluation Chess position is evaluated to assign a value Value = 2.1
Minimax Algorithm Values propagate up to give better estimate
Type A Strategy Examine all variations to a fixed depth
Type B Strategy Examine selected variations to variable depth
First Program Written in 1957, 7 years after Shannon's paper
Alpha Beta Pruning Doubles how deep computers can look ahead
First Milestone Computer defeats 1500 rated player in 1967
The Bet Levy bet a computer could not beat him in 10 years
Levy Wins In 1978 Levy wins the bet
Fredkin Prize $100,000 to beat the world chess champion
Personal Chess Computer Annual sales of $100 million
Garry Kasparov Became world chess champion in 1985
Deep Thought First chip designed to play only chess
Deep Blue IBM takes interest in computer chess
2010 PC chess programs defeat world champion
Future Humans will always enjoy chess
Arimaa Playable with a chess set, but different rules
Bobby Fischer Proposed random initial setup for chess
Aamir Arimaa is aamir backwards with a leading A
Arimaa is Difficult High branching factor, no opening books, few captures
Arimaa Challenge $10,000 to beat top human players before 2020
Arimaa and AI Will require a breakthrough in AI before 2020
Questions More info at www.arimaa.com
Luca Weibel Honors Track: Competitive Programming & Problem Solving Partisan game theory.
Adversarial Search Reference: “Artificial Intelligence: A Modern Approach, 3 rd ed” (Russell and Norvig)
Adversarial Search Board games. Games 2 player zero-sum games Utility values at end of game – equal and opposite Games that are easy to represent Chess.
G5AIAI Introduction to AI Graham Kendall Game Playing Garry Kasparov and Deep Blue. © 1997, GM Gabriel Schwartzman's Chess Camera, courtesy IBM.
CPS 270: Artificial Intelligence Two-player, zero-sum, perfect-information Games Instructor: Vincent Conitzer.
Games and adversarial search. Why study games? Games are a traditional hallmark of intelligence Games are easy to formalize Games can be a good model.
Games and adversarial search. Why study games? Games can be a good model of many competitive activities –Military confrontations, negotiation, auctions,
Today’s Topics Playing Deterministic (no Dice, etc) Games –Mini-max – - pruning –ML and games? 1997: Computer Chess Player (IBM’s Deep Blue) Beat Human.
Artificial Intelligence Game Playing Chapter 6. Outline of this Chapter Introduction Defining a game 2 person games Minimax α-β pruning State of the art.
Games & Adversarial Search Chapter 6 Section 1 – 4.
Mastering Chess An overview of common chess AI Adam Veres.
ICS-270a:Notes 5: 1 Notes 5: Game-Playing ICS 270a Winter 2003.
MIU Mini-Max Graham Kendall Game Playing Garry Kasparov and Deep Blue. © 1997, GM Gabriel Schwartzman's Chess Camera, courtesy IBM.
Parallel Programming in Chess Simulations Tyler Patton.
Lecture 13 Last time: Games, minimax, alpha-beta Today: Finish off games, summary.
1 Adversarial Search Chapter 6 Section 1 – 4 The Master vs Machine: A Video.
Chess Applications:Alpha- Beta Search Greg Parker ‘03 Senior Thesis Advisor: Andrew Appel.
Adversarial Search Chapter 6 Section 1 – 4. Types of Games.
Adversarial Search Chapter 5. Outline Optimal decisions for deterministic, zero-sum game of perfect information: minimax α-β pruning Imperfect, real-time.
AI for Connect-4 (or other 2-player games) Minds and Machines.
Games & Adversarial Search Chapter 5. Games vs. search problems "Unpredictable" opponent specifying a move for every possible opponent’s reply. Time.
Group 1 : Ashutosh Pushkar Ameya Sudhir From. Motivation Game playing was one of the first tasks undertaken in AI Study of games brings us closer.
Game Playing Chapter 6 CS 63 Adapted from materials by Tim Finin, Marie desJardins, and Charles R. Dyer.
Games & Adversarial Search. Game tree (2-player, deterministic, turns) How do we search this tree to find the optimal move?
COMP-4640: Intelligent & Interactive Systems Game Playing A game can be formally defined as a search problem with: -An initial state -a set of operators.
Adversarial Search CSE 473 University of Washington.
CHAPTER 4 PROBABILITY THEORY SEARCH FOR GAMES. Representing Knowledge.
ADVERSARIAL SEARCH Chapter 6 Section 1 – 4. OUTLINE Optimal decisions α-β pruning Imperfect, real-time decisions.
Adversarial Search Chapter 6 Section 1 – 4. Outline Optimal decisions α-β pruning Imperfect, real-time decisions.
An Introduction to Artificial Intelligence Lecture VI: Adversarial Search (Games) Ramin Halavati In which we examine problems.
Adversarial Search Chapter 5 Sections 1 – 4. AI & Expert Systems© Dr. Khalid Kaabneh, AAU Outline Optimal decisions α-β pruning Imperfect, real-time decisions.
By Joseph Tanti FIDE Instructor. Some completely different ways to play chess.
CS 484 – Artificial Intelligence1 Announcements Lab 1 is due today, September 20 Homework 3 due Tuesday, September 25 Current Event Volunteer?
1 Adversarial Search CS 171/271 (Chapter 6) Some text and images in these slides were drawn from Russel & Norvig’s published material.
Games and adversarial search (Chapter 5) World Champion chess player Garry Kasparov is defeated by IBM’s Deep Blue chess-playing computer in a six-game.
Adversarial Search Chapter 6 Sections 1 – 4. Outline Optimal decisions α-β pruning Imperfect, real-time decisions.
Artificial Intelligence for Games Game playing Patrick Olivier
Nigel David Robert Dunk. Introduction What is artificial intelligence? Merriam-Webster says it is a branch of computer science dealing with the simulation.
Game Playing Perfect decisions Heuristically based decisions Pruning search trees Games involving chance.
Adversarial Search: Game Playing Reading: Chapter next time.
Explorations in Artificial Intelligence Prof. Carla P. Gomes Module 5 Adversarial Search (Thanks Meinolf Sellman!)
1 Chapter 6 Game Playing. 2 Chapter 6 Contents l Game Trees l Assumptions l Static evaluation functions l Searching game trees l Minimax l Bounded lookahead.
Adversarial Search Chapter 6. History Much of the work in this area has been motivated by playing chess, which has always been known as a "thinking person's.
MAE 552 – Heuristic Optimization Lecture 28 April 5, 2002 Topic:Chess Programs Utilizing Tree Searches.
Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Ch. 6 –Adversarial Search Thursday –AIMA, Ch. 6 –More Adversarial Search The “Luke.
AI: AlphaGo European champion : Fan Hui A feat previously thought to be at least a decade away!!!
Game Playing 최호연 이춘우. Overview Intro: Games as search problems Perfect decisions in 2-person games Imperfect decisions Alpha-beta pruning.
Computer Chess A natural domain for studying AI n The game is well structured. n Perfect information game. n Early programmers and AI researchers were.
1 Chapter 6 Section 1 – 4 Adversarial Search. 2 Outline Optimal decisions α-β pruning Imperfect, real-time decisions.
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