Opponent behaviour recognition for real-time strategy games
Froduald Kabanza, Philipe Bellefeuille, Francis Bisson, Abder Rezak Benaskeur, Hengameh Irandoust · 2010
In Real-Time Strategy (RTS) video games, players (con-trolled by humans or computers) build structures and recruit armies, fight for space and resources in order to control strate-gic points, destroy the opposing force and ultimately win the game. Players need to predict where and how the opponents will strike in order to best defend themselves. Conversely, as-sessing how the opponents will defend themselves is crucial to mounting a successful attack while exploiting the vulnera-bilities in the opponent’s defence strategy. In this context, to be truly adaptable, computer-controlled players need to rec-ognize their opponents ’ behaviour, their goals, and their plans to achieve those goals. In this paper we analyze the algorith-mic challenges behind behaviour recognition in RTS games and discuss a generic RTS behaviour recognition system that we are developing to address those challenges. The applica-tion domain is that of RTS games, but many of the key points we discuss also apply to other video game genres such as multiplayer first person shooter (FPS) games.