233 search results - page 8 / 47 » Composing and combining policies under the policy machine |
82
Voted
ICML
2003
IEEE
16 years 14 days ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
91
Voted
ICML
2009
IEEE
16 years 14 days ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
115
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ICAC
2008
IEEE
15 years 6 months ago
2008
IEEE
Creating good adaptation policies is critical to building complex autonomic systems since it is such policies that define the system configuration used in any given situation. W...
125
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ICML
1995
IEEE
16 years 14 days ago
1995
IEEE
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
106
Voted
AAAI
2011
13 years 11 months ago
2011
With smart-phones becoming increasingly commonplace, there has been a subsequent surge in applications that continuously track the location of users. However, serious privacy conc...