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Nine Men's Morris Nine Men's Morris

Nine Men's Morris - PowerPoint Presentation

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Uploaded On 2015-09-26

Nine Men's Morris - PPT Presentation

Martin Boyd Christopher Hirunthanakorn Game Overview Two player game RULES Players alternate turns placing pieces on the board If a mill is formed player may remove an opponents piece mill three pieces formed along a line ID: 140876

player game men adaptive game player adaptive men pieces states mill program runs morris state strategy opponent board move

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Slide1

Nine Men's Morris

Martin Boyd

Christopher HirunthanakornSlide2

Game Overview

Two player game

RULES

Players alternate turns placing pieces on the boardIf a mill is formed, player may remove an opponent's piecemill - three pieces formed along a lineAfter both players place nine pieces, players move their pieces to any free adjacent spotThe game is over when a player has less than 3 pieces or no legal moves remainSlide3

ExampleSlide4

Example (continued)Slide5

Game Classification

Determinate

Zero-sum

SymmetricPerfect InformationSequentialNormalSlide6

Background

One of the oldest games played to date

Game board carving from 1400 BCE found in Egypt

Also known as Mill, Merelles, or Cowboy CheckersPopular variants of the game include Three Men's, Six Men's, and Twelve Men's MorrisSlide7

Research Goals/Questions

Look for an optimal strategy for piece placement

Find an optimal strategy for gameplay

Is there a winning strategy for either player?Is the game fair?Slide8

Analyzing the Game

Searched for previous work on the game

Game States and Combinatorics

Created program with a GUIAnalyzed Five Men's Morris Created an Adaptive ProgramCreated an AIUsed python as the programming languageSlide9

Previous Publications

Ralph Gasser (Swiss computer scientist)

Proved that perfect play in Nine Men's Morris results in a draw and is impossible for humans to achieve

Analyzed the midgame and endgame by going through all possible game states and labeling them a win or lose positionDid not provide any advice on the optimal strategy or fairness of the gameSlide10

Five Men's Morris

Players have 5 pieces instead of 9

16 spots instead of 24Slide11

Game States and Combinatorics

A game state is defined as the game board and all relevant information defining it such as Last player to move and position of last move

Board to the right is the game state where player 1 just went but could have placed it on either side

Used combinatorics to estimate the number of game states possible About 1.74 * 10^11 states based on possible combinations of placement (16*15*14*13*12*11*10*9*8*7*6)Can be reduced using symmetry of game states to about 7.26 * 10^8 (31+14*13*12*11*10*9*8*7*6)Slide12

Basic Program Structure

A

1

B

C

D

E

2

3

4

5

B2

E5Slide13

Basic Program Structure

Data of the Game Board is stored in 3 arrays

Basic Array

[A1,A3,A5,B2,B3,B4,C1,C2,C4,C5,D2,D3,D4,E1,E3,E5]Mill Array[[0,A1,A3,A5],[0,B2,B3,B4],...,[0,E1,E3,E5]] Connection Array[[A1,A3,C1,0],[A3,A1,A5,B3],...,[E5,C5,E3,0]]Slide14

Adaptive Program

Runs the Game MANY times

Contains Matchboxes that punish a player if that player loses thus not repeating the same mistake twice.Slide15

Matchboxes

A

E

C

D

B

1

2

3

4

5

A5

C2

B4

C5

D2

C4

D3

D4

E5

MOVESSlide16

Adaptive Program

2 different Adaptive Programs written for Five Men's Morris

Opening Stage Adaptive

Contains a Matchbox for each player to select spotsSecond Stage AdaptiveContains two Matchboxes for each player to move pieces and the other for removing piecesSlide17

Adaptive Results

Opening Stage Adaptive

After 60 million runs (On the last 10 million)

72544 won by Player 144059 won by Player 29883397 end in a drawPlayer 1 has 20% advantage on win/loss

However most opening stages end in draw

Second Stage AdaptiveAfter 10 million runs still dead even

The program requires more runs to draw a conclusion.Slide18

AI Logic (Minimax and Negamax)

AI is based on the game theory decision rule of Minimax and Negamax

Both determine the worth of a game state using a set of conditions

Efficiently searches through possible states and presents the best one.Negamax differs in how it eliminates certain states that can not be achieved to increase search speeds Current State

2

0

2

5

9

1

6

Next State

Next Next StateSlide19

AI Logic (Scoring)

Plays the game more intelligently by choosing the best move from all possible moves for that game board

Moves are scored based on the resultant game board

next to open connection or own piece = +1next to opponent's piece = -1sets up 2/3 parts of a mill = +2blocks opponent's mill = +2makes a mill = +3Slide20

AI Results

Player 1 using AI

,

Player 2 playing randomlyAfter 1000 runs multiple times, Player 1 wins roughly about 70% of the timeBoth players using AIAfter 1000 runs multiple times, neither player has an advantage over the other (around 50% each)AI will require more improvements and test runs to get solid resultsSlide21

General Strategy

Take spots on both rings

Take spots with the most connections

Block your opponent's move in a way that you don't trap yourselfTry to force your opponent to allow you to make a millEx) player 1 takes outside corners and player 2 tries to blockIf possible, set up two potential mills next to each other so that a mill can be made by moving back and forthSlide22

Future Work

Improve AI and adaptive learning programs to be more efficient

Currently the Adaptive takes too long to run through the required number of games

Confirm the patterns found apply to Nine Men's Morris by running the programs on itCome up with a more detailed strategy that will handle every situation