Abstract
In this paper we introduce Stratified Strategy Selection (SSS), a novel search algorithm for micromanaging units in real-time strategy (RTS) games. SSS uses a type system to partition the player's units into types and assumes that units of the same type must follow the same strategy. SSS searches in the state space induced by the type system to select, from a pool of options, a strategy for each unit. Empirical results on a simulator of an RTS game shows that SSS employing either fixed or adaptive type systems is able to substantially outperform state-of-the-art search-based algorithms in combat scenarios with up to 100 units.
Keywords
- Multidisciplinary Topics and Applications: Computer Games
- Multidisciplinary Topics and Applications: Interactive Entertainment
- Agent-based and Multi-agent Systems: Multi-agent Planning
- Planning and Scheduling: Real-time Planning
