EVOLUTIONARY ALGORITHMSVS.POKER GAMES

Yikan Chen (yc2r@virginia.edu)Weikeng Qin (wq7yt@virginia.edu)

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OUTLINE

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Evolutionary Algorithm

Poker!

Artificial Neural

Network

E-ANN

EVOLUTIONARY ALGORITHM

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EVOLUTIONARY ALGORITHM

Evolution Process

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Crossover

Mutation

Natural Selection

Evolutionary Algorithm

EVOLUTIONARY ALGORITHM

Encoding and Crossover

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1 1 1 0 0 1 1 0

0 1 0 0 1 0 1 1

0 0 1 1 0

0 1 0 1 1

0 1 0

1 1 1

EVOLUTIONARY ALGORITHM

Mutation

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1 1 1 0 0 1 1 0

1 1 0 0 0 1 1 1

EVOLUTIONARY ALGORITHM

Natural Selection

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Run the roulette-wheel selection based on the fitness value of candidates

EVOLUTIONARY ALGORITHM

Important Parameters Crossover rate Mutation rate Elite rate Fitness function

Demohttp://userweb.elec.gla.ac.uk/y/yunli/

ga_demo/

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EVOLUTIONARY ALGORITHM & POKER AKQ 2-player game

$1 blinds for each player Player1 bet or fold Player2 call or fold

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EVOLUTIONARY ALGORITHM & POKER Derive the optimal strategy using EA Chromosomal representations

Fij: fold threshold when Pi got Cardj

Fitness functions

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Card1

Card2

Card3

P1 2/3 0 0

P2 1 2/3 0

EVOLUTIONARY ALGORITHM & POKER Fitness functions

Fi: fitness function Wij: money won by candidate I against

candidate j

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EVOLUTIONARY ALGORITHM & POKER

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Decreased fluctuation

Further decreased fluctuation

400-500 generations

Var(f11) ; Var(f22)

Mean(f11);Mean(f22)

Count only wins

.065;

.067.67;.60

Penalize failure

.037;

.035.67;.70

Penalize Failure heavier

.028;

.024.67;.74

EVOLUTIONARY ALGORITHM & POKER Real Texas Hold’em Encoding Strategy (Turn and River)

Hand strength (player confidence) Fraction of opponent raise (opponent

confidence) Total raise (profit)

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EVOLUTIONARY ALGORITHM & POKER Fitness Criterion

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EVOLUTIONARY ALGORITHM & POKER Performance

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ARTIFICIAL NEURAL NETWORK: REVIEW

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ARTIFICIAL NEURAL NETWORK: REVIEW

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∑

w1

w2

wn

b

……

a1

a2

an

1

f output

ARTIFICIAL NEURAL NETWORK: REVIEW

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Inputoutput

Hidden Layer

EvolvingTopology

E-ANN (EVOLUTIONARY ANN)

Simplest Encoding Method

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a b c d d c b a

NEAT E-ANN

http://www.cs.utexas.edu/users/nn/ Neuro Evolution of Augmenting

Topologies Encoding Strategy: Node-based

Neuron gene table Link gene table

Innovation number Global database of innovations Each innovation has unique ID number

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NEAT E-ANN

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NEAT E-ANN

Mutation Perturb weights Add a link gene Add a neuron gene

Crossover By innovation number

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NEAT E-ANN Crossover

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2 3

5

6

4

31 2

5

4

1

11->4

22->4

33->4

42->5

55->4

81->5

11->4

22->4

33->4

42->5

55->4

65->6

76->4

93>5

101->6

NEAT E-ANN Crossover

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2 3

5

6

4

1

81->5

11->4

22->4

33->4

42->5

55->4

65->6

76->4

93>5

101->6

E-ANN & POKER

Simplified Poker Model 1-10 Initial credit: 10 chips One chip ante at the beginning Call, raise (1 chip each time), fold Tournament

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E-ANN & POKER

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Two player game

E-ANN & POKER

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E-ANN & POKER

Four different types of opponents

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Tight Aggressive (TA) Tight Passive (TP)Loose Aggressive (LP) Loose Passive (LP)

E-ANN & POKER

α: min win probability to call β: min win probability to raise

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E-ANN & POKER

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A: player typeB: player action

E-ANN & POKER

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E-ANN & POKER

Bluffing……

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Thanks!