An Alternative Approach for Playing Complex Games like Chess.

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An Alternative Approach for Playing Complex Games
like Chess.
Jan Lemeire May 19th 2008
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Computer versus Brain
Research Topics
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 Approach
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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.

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Game State Evaluation

• All approaches rely on a game state evaluation
• measure goodness of state
• Or
• to select a good move.

My hypothesis is based on a problem with state
evaluation.
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Example fork pattern.
Opportunity! Fork pattern is way to success!
Counter move Fork pattern does not give an
advantage
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Correct evaluation problem

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

For example fork and make chess
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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.

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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.

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New kind of knowledge

• Fork ? win a piece
• Weak kings defense ? successful attack on the
  king
• Pressure ? successful combination

Patterns denote opportunities, advantages have to
be verified.
Alternative Game Playing Approach
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E.g. fork bad defense of the king can we have a
successful attack on the king or get an advantage
by putting pressure on the king bad defense ?
pressure ? advantage
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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
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Hypothesis More efficient than brute force tree
exploration

• Second hypothesis this works if one can quickly
  evaluate interfering patterns

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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 playing
• Humans can reason about a game.

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Hypothesis requires theoretical or experimental
confirmation

• Test
• by simulation of games ? no decisive conclusion
  yet.
• Pattern engine needed that is able to
• Describe patterns
• Recognize patterns
• Extract patterns
• Reason 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?