Asymmetric Action Abstractions for Multi-Unit Control in Adversarial Real-Time Games

Authors

  • Rubens Moraes Universidade Federal de Viçosa
  • Levi Lelis Universidade Federal de Viçosa

Keywords:

real-time strategy games, real-time adversarial planning, action abstractions

Abstract

Action abstractions restrict the number of legal actions available during search in multi-unit real-time adversarial games, thus allowing algorithms to focus their search on a set of promising actions. Optimal strategies derived from un-abstracted spaces are guaranteed to be no worse than optimal strategies derived from action-abstracted spaces. In practice, however, due to real-time constraints and the state space size, one is only able to derive good strategies in un-abstracted spaces in small-scale games. In this paper we introduce search algorithms that use an action abstraction scheme we call asymmetric abstraction. Asymmetric abstractions retain the un-abstracted spaces' theoretical advantage over regularly abstracted spaces while still allowing the search algorithms to derive effective strategies, even in large-scale games. Empirical results on combat scenarios that arise in a real-time strategy game show that our search algorithms are able to substantially outperform state-of-the-art approaches.

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Published

2018-04-25

How to Cite

Moraes, R., & Lelis, L. (2018). Asymmetric Action Abstractions for Multi-Unit Control in Adversarial Real-Time Games. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/11432

Issue

Section

AAAI Technical Track: Game Playing and Interactive Entertainment