Experiments with Game Tree Search in Real-Time Strategy Games
This work addresses a domain-specific challenge for AI in gaming, but it appears incremental as it adapts an existing method to a new context.
The paper tackled the problem of applying game tree search algorithms to real-time strategy (RTS) games by introducing RTMM, a real-time variant of minimax, and evaluated it in two games, showing its applicability but without providing concrete performance numbers.
Game tree search algorithms such as minimax have been used with enormous success in turn-based adversarial games such as Chess or Checkers. However, such algorithms cannot be directly applied to real-time strategy (RTS) games because a number of reasons. For example, minimax assumes a turn-taking game mechanics, not present in RTS games. In this paper we present RTMM, a real-time variant of the standard minimax algorithm, and discuss its applicability in the context of RTS games. We discuss its strengths and weaknesses, and evaluate it in two real-time games.