TotalBotWar: A New Pseudo Real-time Multi-action Game Challenge and Competition for AI
It provides a new platform for testing AI algorithms in complex, partially observable environments, but is incremental as it adapts an existing game series.
The paper introduces TotalBotWar, a pseudo real-time multi-action game challenge based on TotalWar battles, and benchmarks it with initial experiments using different AI agents.
This paper presents TotalBotWar, a new pseudo real-time multi-action challenge for game AI, as well as some initial experiments that benchmark the framework with different agents. The game is based on the real-time battles of the popular TotalWar games series where players manage an army to defeat the opponent's one. In the proposed game, a turn consists of a set of orders to control the units. The number and specific orders that can be performed in a turn vary during the progression of the game. One interesting feature of the game is that if a particular unit does not receive an order in a turn, it will continue performing the action specified in a previous turn. The turn-wise branching factor becomes overwhelming for traditional algorithms and the partial observability of the game state makes the proposed game an interesting platform to test modern AI algorithms.