e-Valuate: A Two-player Game on Arithmetic Expressions -- An Update
Sarang Aravamuthan, Biswajit Ganguly

TL;DR
This paper updates the analysis of e-Valuate, a game on arithmetic expressions, introducing heuristics and variants, and demonstrating improved computational performance and new game applications.
Contribution
It presents new heuristics and domain-specific variants of e-Valuate, enhancing game analysis and computational efficiency.
Findings
Alpha-beta pruning efficiency improved with heuristics
Transposition tables reduce node reevaluation
Maximal partial tiling requires at least 22 dominoes
Abstract
e-Valuate is a game on arithmetic expressions. The players have contrasting roles of maximizing and minimizing the given expression. The maximizer proposes values and the minimizer substitutes them for variables of his choice. When the expression is fully instantiated, its value is compared with a certain minimax value that would result if the players played to their optimal strategies. The winner is declared based on this comparison. We use a game tree to represent the state of the game and show how the minimax value can be computed efficiently using backward induction and alpha-beta pruning. The efficacy of alpha-beta pruning depends on the order in which the nodes are evaluated. Further improvements can be obtained by using transposition tables to prevent reevaluation of the same nodes. We propose a heuristic for node ordering. We show how the use of the heuristic and transposition…
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Taxonomy
TopicsArtificial Intelligence in Games · Game Theory and Applications · Constraint Satisfaction and Optimization
