Opponent Modeling in Real-Time Strategy Games.
Frederik C. Schadd, Sander C. J. Bakkes, Pieter H.M. Spronck · 2007
Real-time strategy games present an environment in which game AI is expected to behave realistically. One feature of realistic behaviour in game AI is the ability to recognise the strategy of the opponent player. This is known as opponent modeling. In this paper, we propose an approach of opponent modeling based on hierarchi-cally structured models. The top-level of the hierarchy can classify the general play style of the opponent. The bottom-level of the hierarchy can classify specific strate-gies that further define the opponent’s behaviour. Ex-periments that test the approach are performed in the RTS game Spring. From our results we may conclude that the approach can be successfully used to classify the strategy of an opponent in the Spring game.