A demonstration of agent learning with action-dependent learning rates in computer role-playing games

Proceedings of the 4th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2008

Volumn , Issue , 2008, Pages 218-219

  Cutumisu, Maria ^a   Szafron, Duane ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AGENT LEARNING; DYNAMIC STRATEGIES; LEARNING RATES; NEVERWINTER NIGHTS; ROLE-PLAYING GAME; SCRIPTING LANGUAGES;

ARTIFICIAL INTELLIGENCE;

HUMAN COMPUTER INTERACTION;

EID: 84883127644     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Bowling, M., and Veloso, M. 2001. Rational and Convergent Learning in Stochastic Games. In Proceedings of the 7th International Joint Conference on AI, 1021-1026.
2. Cutumisu, M., Szafron, D., Bowling, M., and Sutton, R. S. 2008. Agent Learning Using Action-Dependent Learning Rates in Computer Role-Playing Games. In Proceedings of the 4th AIIDE Conference, October 22-24, 2008, Stanford, USA. NWN 2008. http://nwn.bioware.com.
3. NWN Arena. 2008. http://www.cs.unimaas.nl/p.spronck/GameAI/ OnlineAdaptation3.zip.
4. Spronck, P., Sprinkhuizen-Kuyper, I., and Postma, E. 2004. Online Adaptation of Game Opponent AI with Dynamic Scripting. International Journal of Intelligent Games and Simulation 3(1): 45-53.
5. Sutton, R.S. 1992. Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta. In Proceedings of the 10th National Conference on AI, 171-176.
6. Sutton, R.S., and Barto, A.G. eds. 1998. Reinforcement Learning: An Introduction. Cambridge, Mass.: MIT Press.