Balancing multiple sources of reward in reinforcement learning

Advances in Neural Information Processing Systems

Volumn , Issue , 2001, Pages

  Shelton, Christian R ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MULTIPLE COMPONENTS; MULTIPLE REWARDS; MULTIPLE SOURCE; MULTIPLE USER; SCALAR COMPONENT; SCALAR VALUES; SIMULATED ENVIRONMENT; TRADITIONAL REINFORCEMENTS;

REINFORCEMENT LEARNING;

EID: 84899028619     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. C. L. Isbell, C. R. Shelton, M. Kearns, S. Singh, and P. Stone. A social reinforcement learning agent. 2000. submitted to Autonomous Agents 2001.
3. J. Karlsson. Learning to Solve Multiple Goals. PhD thesis, University of Rochester, 1997.
4. M. Kearns, Y. Mansouor, and S. Singh. Fast planning in stochastic games. In Proc. of the I6th Conference on Uncertainty in Artificial Intelligence, 2000.
5. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Proc. of the 11th International Conference on Machine Learning, pages 157-163, 1994.
6. G. Owen. Game Theory. Academic Press, UK, 1995.
7. S. Singh, M. Kearns, and Y. Mansour. Nash convergence of gradient dynamics in general-sum games. In Proc. of the 16th Conference on Uncertainty in Artificial Intelligence, 2000.
8. S. P. Singh. The efficient learning of multiple task sequences. In NIPS, Volume 4, 1992.