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» Optimal Sequential Exploration: A Binary Learning Model
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151views
12 years 6 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
COLT
2008
Springer
13 years 9 months ago
When Random Play is Optimal Against an Adversary
We analyze a sequential game between a Gambler and a Casino. The Gambler allocates bets from a limited budget over a fixed menu of gambling events that are offered at equal time i...
Jacob Abernethy, Manfred K. Warmuth, Joel Yellin
ASPDAC
2004
ACM
120views Hardware» more  ASPDAC 2004»
14 years 1 months ago
Compiler based exploration of DSP energy savings by SIMD operations
— The growing use of digital signal processors (DSPs) in embedded systems necessitates the use of optimizing compilers supporting their special architecture features. Beside the ...
Markus Lorenz, Peter Marwedel, Thorsten Dräge...
ICML
2010
IEEE
13 years 8 months ago
Convergence, Targeted Optimality, and Safety in Multiagent Learning
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...
Doran Chakraborty, Peter Stone