Potential-field based navigation in StarCraft

Abstract

Real-Time Strategy (Rts) games are a sub-genre of strategy games typically taking place in a war setting. Rts games provide a rich challenge for both human- and computer players (bots). Each player has a number of workers for gathering resources to be able to construct new buildings, train additional workers, build combat units and do research to unlock more powerful units or abilities. The goal is to create a strong army and destroy the bases of the opponent(s). Armies usually consists of a large number of units which must be able to navigate around the game world. The highly dynamic and real-time aspects of Rts games make pathfinding a challenging task for bots. Typically it is handled using pathfinding algorithms such as A*, which without adaptions does not cope very well with dynamic worlds. In this paper we show how a bot for StarCraft uses a combination of A* and potential fields to better handle the dynamic aspects of the game.