449 search results - page 20 / 90 » Finding Structure in Reinforcement Learning |
145
Voted
CAMP
2005
IEEE
15 years 9 months ago
2005
IEEE
— For a peer-to-peer (P2P) system holding massive amount of data, an efficient and scalable search for resource sharing is a key determinant to its practical usage. Unstructured...
133
Voted
ICANN
2010
Springer
15 years 4 months ago
2010
Springer
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
125
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ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
112
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ATAL
2008
Springer
15 years 5 months ago
2008
Springer
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...
117
Voted
COLT
2008
Springer
15 years 5 months ago
2008
Springer
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...