An Alternative Approach for Playing Complex Games like Chess.

An Alternative Approach for Playing Complex Games like Chess.

1Alternative Game Playing Approach

Jan LemeireMay 19th 2008

Pag.Jan Lemeire / 142Alternative Game Playing Approach

Research TopicsComputer versus Brain

Deep Blue: 600 million evaluations/second

Chess experts: 10 patterns/second

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Brute force chess playing

Most succesful!

Evaluation of future states

Alternative Game Playing Approach3

White plays

Black plays

White plays

Black plays


Alternative game playing approaches

Decision-making: used to map states to operators.Explanation-Based Learning (EBL): try to learn the states that lead to advantageous situations.States are identified by patterns.



Game State Evaluation


All approaches rely on a game state evaluation:– measure ‘goodness’ of stateOr– to select a good move.

My hypothesis is based on a problem with state evaluation.

Pag.Jan Lemeire / 146Alternative Game Playing Approach

Example: fork pattern.

Opportunity!Fork pattern is way to

success!

Counter move…Fork pattern does

not give an advantage…


Correct evaluation problem

Consider two relevant patterns, P1 and P2 evaluation = f(P1, P2) 4 regions in state space should be considered:


P1 & P2

P1 & P2

P1 & P2

P1 & P2

W: advantageous for whiteB: advantageous for black0: no advantageFor example ‘fork’ and ‘make chess’


Correct evaluation problem

Evaluation = f(features or patterns).

One has to capture all situations in which the pattern leads to a successful outcome, all counter plans have to be excluded.Evaluation of pattern combinations heavily depends on game context!Features alone do not give us the right information.



Known problem in literature

Deep Blue relied on looking as far as possible into the future and just a simple state evaluation.

“However, even simple patterns like a knight fork are non-trivial to formalize…” Fürnkranz 2001.

“Learning too many too specialized rules with explanation-based learning”, Minton 1984, Epstein, Gelfand and Joanna Lesniak 1996 (HOYLE pattern-based learning).

“Even in simple games, such as tic-tac-toe, 45 concepts were learned with 52 exception clauses”, Fawcett and Utgoff 1991.

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Hypothesis

“The impact of a pattern on the outcome of the game entirely depends on whether or not some states, called the effects, are attained during the continuation of the game.”



New kind of knowledge

Fork win a pieceWeak king’s defense successful attack on the king Pressure successful combination

Alternative Game Playing Approach11

Patterns denote opportunities, advantages have to be verified.


Alternative game playing


White recognizes pattern 1:

White has to check in game tree whether - a positive effect can be attained: - black can neutralize pattern 1:

1

1

1

Hypothesis:More efficient than brute

force tree exploration


Similar to human game playing!

Chess experts rely on falsification (Cowley and Byrne, 2004).Humans can easily recognize and identify patterns, but have difficulties formally defining them.Humans can pinpoint the patterns that were decisive in a game, can answer why-questions.

not by current computer game playingHumans can reason about a game.



Hypothesis requires theoretical or experimental confirmation…


Test by simulation of games no decisive conclusion yet.

Pattern engine needed that is able to:Describe patternsRecognize patternsExtract patternsReason with patterns

“White attacks two black pieces with a fork, one of the pieces can make chess. White thus has to move its king and black can bring his second piece into safety.”

Theoretical proof?

An Alternative Approach for Playing Complex Games like Chess.

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