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A Proposed Heuristic for a Computer Chess Program (John L. Jerz)

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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

652k download - pdf version
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1 November, 2009 - A Proposed Heuristic For a Computer Chess Program

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What if we applied Dr. Eliyahu M. Goldratt's Theory of Constraints and Thinking Process to a computer chess program?
 
Theory of Constraints is a thinking process that requires people to make logical decisions based on the current environment using key barometers... the barometer must correctly model the system and reflect the constrained activities of the organization.[D. Smith, The Measurement Nightmare, p.77]
 
The common theme running through all TOC applications is constraint management. Because constraints are what keep an enterprise from reaching its goal, global optimization of enterprises has to address constraints. [John Ricketts, Reaching the Goal, p.63]
 
Constraints can be considered as pieces of partial information. Constraints describe properties of unknown objects and relationships between them... Constraints allow for a finite representation and efficient processing of possibly infinite relations. [Fruhwirth, Abdennadher, Essentials of Constraint Programming, p.1]

We might also consider the concept of Resilience and construct positions that are full of capacity to respond to the unexpected:

p.3"Consider Pat Lagadec's vivid words: 'The ability to deal with a crisis situation is largely dependent on the structures that have been developed before chaos arrives. The event can in some way be considered as an abrupt and brutal audit: at a moment's notice, everything that was left unprepared becomes a complex problem, and every weakness comes rushing to the forefront.' [Preventing Chaos in a Crisis, p.54, Patrick Lagadec, Jocelyn Phelps, 1993]" Weik, Sutcliffe, Managing the Unexpected

p.8"Small events have large consequences. Small discrepancies give off small clues that are hard to spot but easy to treat if they are spotted. When clues become much more visible, they are that much harder to treat. Managing the unexpected often means that people have to make strong responses to weak signals, something that is counterintuitive and not very 'heroic.' Normally, we make weak responses to weak signals and strong responses to strong signals... systems that mismanage the unexpected tend to ignore small failures, accept simple diagnoses, take frontline operations for granted, neglect capabilities for resilience, and defer to authorities rather than experts." Weik, Sutcliffe, Managing the Unexpected

Wikipedia article on Theory of Constraints

Read more about the Theory of Constraints

Read more about Resilience

Read more about Systems Thinking

Additional Quotations

This interesting idea for an evaluation function for a computer chess program is worth reading if you enjoy looking at new ideas in the field of computer chess. We use the future mobility of the chess pieces and the ability of the lower-value enemy pieces to restrict mobility to better estimate positional pressure and focus our search efforts.
 
This paper can be considered to be an extension of the ideas of Dan Heisman, M. Botvinnik, Eliyahu M. Goldratt, Judea Pearl, Rina Dichter, Aron Katsenelinboigen, Norman Garmezy and others.
 
Abstract:
How might we create an evaluation function for a computer chess program that plays a stronger positional game of chess? A new heuristic for estimating the positional pressure produced by chess pieces is proposed. The identification and management of stressors and the construction of resilient positions allow effective cut-offs for less-promising game continuations due to the presence of adaptive capacity. We calculate and maintain a database of potential mobility for each chess piece 3 moves into the future, for each position we evaluate in our search tree. We determine the restrictions placed on the future mobility of the pieces based on the attack paths of the lower-valued enemy pieces.  Initial results are presented.
 
keywords: complexity, chess, game theory, constraints, heuristics, planning, measurement, diagnostic test, resilience
 

The links below are to individual chapters of an older version the "Proposed Heuristic" paper. The pdf document above represents the current version.

Chapter 1 - Introduction

Chapter 2 - An Explanation of the Proposed Heuristic

Chapter 3 - A Specification for an Evaluation Function

Chapter 4 - A Refinement of the Search Process

Chapter 5 - A Ton of Other Things

Chapter 6 - Supporting Quotations from Published Works

Chapter 7 - Summary

How to Measure Anything (Hubbard, 2007)

Appendix

My Style of Thinking

Problem Solving and the Gathering of Diagnostic Information (John L. Jerz)

A Concept of Strategy Useful for Computer Game Playing (John L. Jerz)

Experimental Results

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Botvinnik-Capablanca, Rotterdam, 1938, white to move

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Computer-Person, Chess Skill in Man and Machine, p. 144 (note corrected diagram)

White "Safety Table" for above position
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Compare with black constraint map...

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