A Dynamical Systems Approach for Static Evaluation in Go

TL;DR

This paper introduces a novel dynamical systems approach to static evaluation in Go, aiming to enhance Monte Carlo tree search by modeling static evaluation dynamically.

Contribution

It presents a new method of static evaluation using dynamical systems, expanding the tools available for game tree search algorithms.

Findings

Demonstrates the general suitability of the dynamical systems approach

Discusses strengths and weaknesses of the method

Provides a theoretical foundation for static evaluation in Go

Abstract

In the paper arguments are given why the concept of static evaluation has the potential to be a useful extension to Monte Carlo tree search. A new concept of modeling static evaluation through a dynamical system is introduced and strengths and weaknesses are discussed. The general suitability of this approach is demonstrated.