Information and Search in Computer Chess

TL;DR

This paper introduces an information theory-based model for computer chess search, proposing a partial depth scheme that allocates more resources to high-information lines, improving search efficiency.

Contribution

It presents a novel mathematical model for partial depth search in chess, with an implementation and experimental validation demonstrating improved search performance.

Findings

Allocating more search resources to high-information lines enhances efficiency

The partial depth scheme improves search performance without additional heuristics

Experimental results confirm the effectiveness of the information-based search strategy

Abstract

The article describes a model of chess based on information theory. A mathematical model of the partial depth scheme is outlined and a formula for the partial depth added for each ply is calculated from the principles of the model. An implementation of alpha-beta with partial depth is given. The method is tested using an experimental strategy having as objective to show the effect of allocation of a higher amount of search resources on areas of the search tree with higher information. The search proceeds in the direction of lines with higher information gain. The effects on search performance of allocating higher search resources on lines with higher information gain are tested experimentaly and conclusive results are obtained. In order to isolate the effects of the partial depth scheme no other heuristic is used.