TY - GEN
T1 - Hierarchical controller learning in a first-person shooter
AU - Van Hoorn, Niels
AU - Togelius, Julian
AU - Schmidhuber, Jürgen
N1 - Generated from Scopus record by KAUST IRTS on 2022-09-14
PY - 2009/12/14
Y1 - 2009/12/14
N2 - We describe the architecture of a hierarchical learning-based controller for bots in the First-Person Shooter (FPS) game Unreal Tournament 2004. The controller is inspired by the subsumption architecture commonly used in behaviour-based robotics. A behaviour selector decides which of three sub-controllers gets to control the bot at each time step. Each controller is implemented as a recurrent neural network, and trained with artificial evolution to perform respectively combat, exploration and path following. The behaviour selector is trained with a multiobjective evolutionary algorithm to achieve an effective balancing of the lower-level behaviours. We argue that FPS games provide good environments for studying the learning of complex behaviours, and that the methods proposed here can help developing interesting opponents for games. ©2009 IEEE.
AB - We describe the architecture of a hierarchical learning-based controller for bots in the First-Person Shooter (FPS) game Unreal Tournament 2004. The controller is inspired by the subsumption architecture commonly used in behaviour-based robotics. A behaviour selector decides which of three sub-controllers gets to control the bot at each time step. Each controller is implemented as a recurrent neural network, and trained with artificial evolution to perform respectively combat, exploration and path following. The behaviour selector is trained with a multiobjective evolutionary algorithm to achieve an effective balancing of the lower-level behaviours. We argue that FPS games provide good environments for studying the learning of complex behaviours, and that the methods proposed here can help developing interesting opponents for games. ©2009 IEEE.
UR - http://ieeexplore.ieee.org/document/5286463/
UR - http://www.scopus.com/inward/record.url?scp=71549132227&partnerID=8YFLogxK
U2 - 10.1109/CIG.2009.5286463
DO - 10.1109/CIG.2009.5286463
M3 - Conference contribution
SN - 9781424448159
SP - 294
EP - 301
BT - CIG2009 - 2009 IEEE Symposium on Computational Intelligence and Games
ER -