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» Approximation algorithms for budgeted learning problems
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IJCAI
2003
14 years 11 months ago
Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
We present a new algorithm, GM-Sarsa(0), for finding approximate solutions to multiple-goal reinforcement learning problems that are modeled as composite Markov decision processe...
Nathan Sprague, Dana H. Ballard
GECCO
2006
Springer
142views Optimization» more  GECCO 2006»
15 years 1 months ago
Classifier prediction based on tile coding
This paper introduces XCSF extended with tile coding prediction: each classifier implements a tile coding approximator; the genetic algorithm is used to adapt both classifier cond...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
ATAL
2008
Springer
14 years 11 months ago
Sequential decision making in repeated coalition formation under uncertainty
The problem of coalition formation when agents are uncertain about the types or capabilities of their potential partners is a critical one. In [3] a Bayesian reinforcement learnin...
Georgios Chalkiadakis, Craig Boutilier
FLAIRS
2003
14 years 11 months ago
Sample Complexity of Real-Coded Evolutionary Algorithms
Researchers studying Evolutionary Algorithms and their applications have always been confronted with the sample complexity problem. The relationship between population size and gl...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
FOCS
2008
IEEE
15 years 4 months ago
What Can We Learn Privately?
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...