Title :
Reactive planning idioms for multi-scale game AI
Author :
Weber, Ben G. ; Mawhorter, Peter ; Mateas, Michael ; Jhala, Arnav
Author_Institution :
Expressive Intell. Studio, Univ. of California, Santa Cruz, CA, USA
Abstract :
Many modern games provide environments in which agents perform decision making at several levels of granularity. In the domain of real-time strategy games, an effective agent must make high-level strategic decisions while simultaneously controlling individual units in battle. We advocate reactive planning as a powerful technique for building multi-scale game AI and demonstrate that it enables the specification of complex, real-time agents in a unified agent architecture. We present several idioms used to enable authoring of an agent that concurrently pursues strategic and tactical goals, and an agent for playing the real-time strategy game StarCraft that uses these design patterns.
Keywords :
artificial intelligence; behavioural sciences computing; computer games; decision making; multi-agent systems; StarCraft; decision making; effective agent; high-level strategic decision; multiscale game AI; reactive planning idiom; real-time strategy game; unified agent architecture; Artificial intelligence; Buildings; Cognition; Context; Games; Planning; Real time systems;
Conference_Titel :
Computational Intelligence and Games (CIG), 2010 IEEE Symposium on
Conference_Location :
Dublin
Print_ISBN :
978-1-4244-6295-7
Electronic_ISBN :
978-1-4244-6296-4
DOI :
10.1109/ITW.2010.5593363