1 Evaluation Function for Computer Go. 2 Game Objective Surrounding most area on the boardSurrounding most area on the board.

Slides:



Advertisements
Similar presentations
Fuzzy Reasoning in Computer Go Opening Stage Strategy P.Lekhavat and C.J.Hinde.
Advertisements

DESCRIPTION: China, one of the world's oldest civilizations, consists of states and cultures dating back more than six millennia. This is an abstract.
Learning in Computer Go David Silver. The Problem Large state space  Approximately states  Game tree of about nodes  Branching factor.
The Game of Go Go is an ancient Chinese board game that is believed to be 2,000 to 4,000 years old. Anton Ninno, OCM-BOCES
Martin Boyd Christopher Hirunthanakorn
Playing Tic Tac Toe with Neural Networks Justin Herbrand CS/ECE/ME 539.
Minimax and Alpha-Beta Reduction Borrows from Spring 2006 CS 440 Lecture Slides.
Place captured red pieces here Place captured yellow pieces here To use as Kings Rules New Game Exit Left mouse click on piece – drag to desired location.
Abstract Proof Search Studied by Tristan Cazenave Surveyed by Akihiro Kishimoto.
Life in the Game of Go David B. Benson Surveyed by Akihiro Kishimoto.
Mathematical Morphology Applied to Computer Go Author: Bruno Bouzy Presenter: Ling Zhao June 30, 2004.
The Move Decision Strategy of Indigo Author: Bruno Bouzy Presented by: Ling Zhao University of Alberta March 7, 2007.
Honte, a Go-Playing Program Using Neural Nets Frederik Dahl.
Combining Tactical Search and Monte-Carlo in the Game of Go Presenter: Ling Zhao University of Alberta November 1, 2005 by Tristan Cazenave & Bernard Helmstetter.
Learning Shape in Computer Go David Silver. A brief introduction to Go Black and white take turns to place down stones Once played, a stone cannot move.
Reinforcement Learning of Local Shape in the Game of Atari-Go David Silver.
Metarules To Improve Tactical Go Knowledge By Tristan Cazenave Presented by Leaf Wednesday, April 28 th, 2004.
And Just Games etc.. EVOLUTION OF COMPUTER GAMES PongOdyssey Beginning of the use of microprocessors ATARI VCS system bit.
Playing Konane Mathematically with Combinatorial Game Theory
Evolution and Coevolution of Artificial Neural Networks playing Go Thesis by Peter Maier, Salzburg, April 2004 Additional paper used Computer Go, by Martin.
Thoughts on AI Will computers ever be intelligent? Really intelligent? Tasks that previously were thought to require intelligence: adding and subtracting.
RULES Each player begins the game with twelve normal pieces (either white or black). The pieces are automatically set in their proper positions. The object.
Inside HARUKA Written by Ryuichi Kawa Surveyed by Akihiro Kishimto.
1 Game Playing Chapter 6 (supplement) Various deterministic board games Additional references for the slides: Luger’s AI book (2005). Robert Wilensky’s.
1 Solving Ponnuki-Go on Small Board Paper: Solving Ponnuki-Go on small board Authors: Erik van der Werf, Jos Uiterwijk, Jaap van den Herik Presented by:
Adversarial Search: Game Playing Reading: Chess paper.
Monte Carlo Go Has a Way to Go Haruhiro Yoshimoto (*1) Kazuki Yoshizoe (*1) Tomoyuki Kaneko (*1) Akihiro Kishimoto (*2) Kenjiro Taura (*1) (*1)University.
Othello Sean Farrell June 29, Othello Two-player game played on 8x8 board All pieces have one white side and one black side Initial board setup.
Multipurpose Adversary Planning in the Game of Go Ph.D thesis by Shui Hu Presenter: Ling Zhao Date: November 18, 2002.
1 An Open Boundary Safety-of- Territory Solver for the Game of Go Author: Xiaozhen Niu, Martin Mueller Dept of Computing Science University of Alberta.
Reinforcement Learning of Local Shape in the Game of Atari-Go David Silver.
The Game of Go Go is an ancient Chinese board game that is believed to be 2,000 to 4,000 years old. Anton Ninno, OCM-BOCES
Corea Japan China WeiqiGoBaduk. The Go is one of the oldest board game in the world. Its true origins are unknown, though it almost certainly originated.
Wei Qi, Baduk, Go a game of strategy
Go An ancient Oriental board game Andrew Simons. Introduction 2 player game of skill. Popular in the Far East, growing in the West. Simple rules, extremely.
Introduction Many decision making problems in real life
Artificial Intelligence in Games CA107 Topics in Computing Dr. David Sinclair School of Computer Applications
By: Joe Merullo Julia Stone and Olivia Pollock. Who plays the game? The game is played by two players who alternately place black and white stones on.
Computer Go : A Go player Rohit Gurjar CS365 Project Proposal, IIT Kanpur Guided By – Prof. Amitabha Mukerjee.
Development of a Machine-Learning-Based AI For Go By Justin Park.
Renju Presented by JungYun Lo National Dong Hwa University Department of Computer Science and Information Engineering Artificial Intelligence Laboratory.
Position Evaluation in Computer Go Martin Muller Dept. of Computer Science and Information Engineering National Dong Hwa University Reporter : Lo Jung-Yun.
 Summary  How to Play Go  Project Details  Demo  Results  Conclusions.
Temple University QUALITY ASSESSMENT OF SEARCH TERMS IN SPOKEN TERM DETECTION Amir Harati and Joseph Picone, PhD Department of Electrical and Computer.
An Overview of Intrusion Detection Using Soft Computing Archana Sapkota Palden Lama CS591 Fall 2009.
CodeVita Season III (2014 – 2015 Season).
Othello Playing AI Matt Smith. Othello 8x8 Board game 8x8 Board game Try to outflank opponents pieces Try to outflank opponents pieces Winner ends up.
Computer Go : A Go player Rohit Gurjar CS365 Project Presentation, IIT Kanpur Guided By – Prof. Amitabha Mukerjee.
Well Posed Learning Problems Must identify the following 3 features –Learning Task: the thing you want to learn. –Performance measure: must know when you.
Senior Project Poster Day 2007, CIS Dept. University of Pennsylvania Reversi Meng Tran Faculty Advisor: Dr. Barry Silverman Strategies: l Corners t Corners.
Lecture 2 Applications of Propositional Logic. Translating English into Logic " The right of the people to be secure in their persons, houses, papers,
IWEC20021 Threat Stacks to Guide Pruning and Search Extensions in Shogi Reijer Grimbergen Department of Information Science Saga University, Japan.
Blondie24 Presented by Adam Duffy and Josh Hill. Overview Introduction to new concepts Design of Blondie24 Testing and results Other approaches to checkers.
SAL: A Game Learning Machine Joel Paulson & Brian Lanners.
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.
Parallelization in Computer Board Games Ian Princivalli.
Year 11 Intermediate GCSE Course Work Borders Piece No 2 Of 2.
Learning to Play the Game of GO Lei Li Computer Science Department May 3, 2007.
Playing Tic-Tac-Toe with Neural Networks
Well Posed Learning Problems Must identify the following 3 features –Learning Task: the thing you want to learn. –Performance measure: must know when you.
Spanish Traditional Games Example. Marbles Objective you keep marbles that you win. You win the opponent´s marbles by hitting them after putting your.
A Scalable Machine Learning Approach to Go Pierre Baldi and Lin Wu UC Irvine.
AI Overview Logical and Artificial Intelligence in Games Lecture 1.
Understanding AlphaGo. Go Overview Originated in ancient China 2,500 years ago Two players game Goal - surround more territory than the opponent 19X19.
Mastering the game of Go with deep neural network and tree search
RESEARCH APPROACH.
AlphaGo and learning methods
AlphaGO from Google DeepMind in 2016, beat human grandmasters
AlphaGo and learning methods
The connected word recognition problem Problem definition: Given a fluently spoken sequence of words, how can we determine the optimum match in terms.
Presentation transcript:

1 Evaluation Function for Computer Go

2 Game Objective Surrounding most area on the boardSurrounding most area on the board

3 Game Stages Opening stage Middle stage Ending stage

4 Opening game stage Establish groupsEstablish groups Extend from own groupExtend from own group Prevent extension from opponent groupPrevent extension from opponent group Reinforce weak groupReinforce weak group Threaten invasion to opponent groupThreaten invasion to opponent group

5 Rules overview through a game (opening 1) Black and White move alternately by putting one stone on an intersection of the board.

6 Rules overview through a game (opening 2) Black and White aims at surrounding large « zones »

7 Rules overview through a game A white stone is put into « atari » : it has only one liberty (empty intersection) left.

8 CIG07 Hawaii Honolulu 8 Rules overview through a game (defense) White plays to connect the one-liberty stone yielding a four-stone white string with 5 liberties.

9 Rules overview through a game (atari 2) It is White’s turn. One black stone is atari.

10 Rules overview through a game White plays on the last liberty of the black stone which is removed

11 Human reasoning Territory Potential Urgent Move Large Move Framework

12 Drawing Border

13 Territory and Potential

14 Stones potential Zobrist A (1970)

15 Hybrid System Future development Search tree Pattern recognition Fuzzy reasoning Neural network Genetic algorithm

16 Fuzzy Influence Conventional method Fuzzy Influence

17 Middle game stage Invade opponent territory Defence their own territory

18 End game stage Close the gap between each groups