Tribes: A New Turn-Based Strategy Game for AI Research

Authors

  • Diego Perez-Liebana Queen Mary University of London
  • Yu-Jhen Hsu Queen Mary University of London
  • Stavros Emmanouilidis Queen Mary University of London
  • Bobby Dewan Akram Khaleque Queen Mary University of London
  • Raluca D. Gaina Queen Mary University of London

Abstract

This paper introduces Tribes, a new turn-based strategy game framework. Tribes is a multi-player, multi-agent, stochastic and partially observable game that involves strategic and tactical combat decisions. A good playing strategy requires the management of a technology tree, build orders and economy. The framework provides a Forward Model, which can be used by Statistical Forward Planning methods. This paper describes the framework and the opportunities for Game AI research it brings. We further provide an analysis on the action space of this game, as well as benchmarking a series of agents (rule based, one step look-ahead, Monte Carlo, Monte Carlo Tree Search, and Rolling Horizon Evolution) to study their relative playing strength. Results show that although some of these agents can play at a decent level, they are still far from human playing strength.

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Published

2020-10-01

How to Cite

Perez-Liebana, D., Hsu, Y.-J., Emmanouilidis, S., Khaleque, B., & Gaina, R. (2020). Tribes: A New Turn-Based Strategy Game for AI Research. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 16(1), 252-258. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/7438