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2013/05/08, MC103, 12 - 12:30

Evolving Strategies for a Turn-Based Game: Practical and Theoretical Issues
Bentley James Oakes , McGill SOCS

Area: Computer Game Design

Abstract:

Video games often have challenging and exciting computer-controlled opponents to play against a human player. However, creating a artificial intelligence (AI) to operate these opponents requires significant development effort by both programmers and game designers. One solution is to use automated processes to evaluate and improve the strength of AIs, and adapt them to changing game maps or mechanics.

This seminar will present ongoing work into the application of genetic algorithms to the AI of Battle for Wesnoth, a popular turn-based strategy game. AI strategies are represented by a tree with action nodes, based on the behaviour tree formalism. These strategies were then evaluated in a Battle for Wesnoth game, in order to obtain a metric of their performance. The genetic algorithm then preferentially selected and combined strategies that performed well, allowing elements from strong strategies to transfer into other strategies. By iterating this process, this algorithm produced strategies that are stronger than the starting strategies.

An overview of genetic algorithms will be provided at the start of the seminar, followed by a short discussion on the difficulty of evaluating AI performance. Preliminary results from this work will then be presented, including the strength of automatically-generated strategies versus hand-built strategies.