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Statistical analysis of the relative strength of chess positions

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Abstract

The statistical value of a piece on its occupied square of origin is extended to those squares controlled by the piece. A cumulative strength metric applies to each square controlled by a piece. The computer model, Relative Strength (RS), predicts the next move in an opening example from the world computer chess championship. A predictive rate is significant. RS is a teaching aid for recognition of tactical chess patterns based on positional patterns. From implementation of RS, recent advances in external computer storage of chess positions include invention of the radix hash sort.

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References

  1. C. James, in Statistical Analysis of the Relative Strength of Chess Positions. 7th International Conference on Pattern Recognition and Image Analysis: New Information Technologies, PRIA-7-2004 (St. Petersburg Electrotechnical University, Russian Federation, October 18–23, 2004), vol. III. pp. 702–705.

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  2. C. James III, B-Tree Database for the Relative Strength of Chess Positions (Colorado Chess Informant, Denver, Colorado, October, 2004), vol. 31. no. 3. pp, 21–23.

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Authors and Affiliations

  1. Principal Scientist, CEC Services, LLC, 1613 Morning Dr, Loveland, CO, 80538-4410, USA

    C. James

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  1. C. James
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Correspondence to C. James.

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Colin James III was born in 1950. He received a BA from The Colorado College in 1972 and a Teaching Certificate in 1974. He received a PhD from Pacific Western University in 1998. His dissertation was about his invention of using logic tables of programmable switches with structured query language to instruct relational databases engines what to do next. He is Principal Scientific of CEC Services, LLC (www.cec-services.com) that specializes in software development for real time database applications for banking, government, and telecommunications and software life cycle management. He was one of the first 500 to learn Dartmouth BASIC in 1964.

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James, C. Statistical analysis of the relative strength of chess positions. Pattern Recognit. Image Anal. 17, 651–662 (2007). https://doi.org/10.1134/S1054661807040268

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  • DOI: https://doi.org/10.1134/S1054661807040268

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