Exploration-exploitation tradeoffs for experts algorithms in reactive environments

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages

  De Farias, Daniela Pucci ^a   Megiddo, Nimrod ^b  

^a Massachusetts Institute of Technology Cambridge   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BALANCE EXPLORATION; EXPLORATION EXPLOITATIONS; EXPLORATION PHASIS; PERFORMANCE BOUNDS;

ALGORITHMS;

EID: 84898942543     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. Auer, P., Cesa-Bianchi, N., Freund, Y. and Schapire, R.E. (1995) Gambling in a rigged casino: The adversarial multi-armed bandit problem. In Proc. 36th Annual IEEE Symp. on Foundations of Computer Science, pp. 322.331, Los Alamitos, CA: IEEE Computer Society Press.
2. de Farias, D. P. and Megiddo, N. (2004) How to Combine Expert (and Novice) Advice when Actions Impact the Environment. In Advances in Neural Information Processing Systems 16, S. Thrun, L. Saul and B. Scholkopf, Eds., Cambridge, MA:MIT Press. http://books.nips.cc/papers/files/nips16/NIPS2003CN09. pdf.
3. Freund, Y. and Schapire, R.E. (1999) Adaptive game playing using multiplicative weights. Games and Economic Behavior 29:79.103.
4. Littlestone, N. and Warmuth, M.K. (1994) The weighted majority algorithm. Information and Computation 108 (2):212-261.