Reinforcement learning as a context for integrating AI research

AAAI Fall Symposium - Technical Report

Volumn FS-04-01, Issue , 2004, Pages 44-46

  Hibbard, Bill ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 32844469918     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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3. Carpenter, G., and Grossberg, S. 2003. Adaptive Resonance Theory. In Handbook of Brain Theory and Neural Networks, Second Edition, Arbib, M., ed. Cambridge, Mass.: MIT Press.
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5. Jackendoff, R. 2002. Foundations of Language. New York: Oxford University Press.
6. Jackendoff, R. Language, Culture, Consciousness: Essays on Mental Structure. Cambridge, Mass.: MIT Press. Forthcoming.
7. Koch, C. 2004. The Quest for Consciousness: a Neurobiological Approach. Englewood, Colorado: Roberts and Co.
8. Minsky, M., Singh P. and Sloman A. 2004. The St. Thomas common sense symposium: designing architectures for human-level intelligence. AI Magazine 25(2): 113-124.
9. Sandberg, A. 2003. Bayesian Attractor Neural Network Models of Memory. Ph.D. diss. Institutionen foer Numerisk Analys och Datalogi, Stockholms Universitet.
10. Seymour, B., O'Doherty, J., Dayan, P., Koltzenburg, M., Jones, A., Dolan, R., Fristen, K., and Frackowiak, R. 2004. Temporal difference models describe higher-order learning in humans. Nature 429, 664-667.
11. Sutton, R., and Barto, A. 1998. Reinforcement Learning: An Introduction. Cambridge, Mass.: MIT Press.