CWU Chess: A Distributed Adaptive Chess Program

People

Computer Science Department

Mentor: Razvan Andonie, Ph.D.

Alumni

Ashur Odah (graduated 2004)

Pushpinder Heer (graduated 2004)

Joseph Lemnley (graduated 2006)

Jonathan Widger (graduated 2006)

Berk Erkul (graduated 2007)

Lukas Magill (graduated 2008)

Central Washington University Campus

Writing a chess program is a notoriously difficult task. Even the best chess programs will rarely win a match against the best human players. The most obvious method for winning a chess game would be to calculate every possible move tree until the closest checkmate is found. Unfortunately, this method would take more computing power than we are likely to have for decades.

Our solution is to develop an adaptive program that uses a genetic algorithm in combination with a neural network that can learn after each game it plays. The entire genetic algorithm/neural network component is part of the evaluation function used to rank each board. Given a board configuration, ten attributes are evaluated each of which is used as the input to the neural network. The weights used in the neural network are optimized using the genetic algorithm. Each time the evaluation function is called, the neural network calculates the value for a given board configuration which will then be used in a recursive search algorithm that uses Alpha-Beta pruning. The weights are adjusted at the end of the game based on its outcome. Work on parallelizing the alpha beta function to achieve greater search depths is partly complete. Our final goal is a fully distributed chess program which learns after each game it plays and analyzes in parallel strategies.

Originally a final project in the CS457 Computational Intelligence course by Ashur Odah, Pushpinder Heer, and Joe Lemley, the CWU Chess program has turned in to a tradition for emerging research students.

Goals

There are several long term goals for the project: creating a chess program that was capable of learning though play, building a platform for future exploration of advanced computer science concepts by students at CWU, and to utilize the power of a network of computers to achieve maximal performance.

Short term goals include:

	Evaluation function improvements
	Preset player profiles
	Ability to play against a humans

Publications and Presentations

	Lukas Magill, Joseph Lemley, Jonathan Widger, Berk Erkul. Fuzzy ARTMAP for chess artificial intelligence, Symposium on University Research and Creative Expression (SOURCE 2006), Ellensburg, May 18, 2006.
	Joseph Lemley, Jonathan Widger. An Adaptive Chess Program Distributed Over A Network of Workstations, Symposium on University Research and Creative Expression (SOURCE 2005), Ellensburg, May 19, 2005 - Outstanding Undergraduate Student Oral Presentations Award.
	Ashur Odah, Pushpinder Heer, Joe Lemley. CWU-Chess - An Adaptive Chess Program, Student Poster Session of the Sixth Annual Northwestern Regional Conference of the Consortium for Computing Sciences in Colleges, Willamette University, Salem, Oregon, October 8 & 9, 2004.