4446 search results - page 492 / 890 » Learning Observer Agents |
197
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SMC
2007
IEEE
16 years 1 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
149
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AAAI
2008
15 years 9 months ago
2008
Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a local...
191
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ATAL
2008
Springer
15 years 8 months ago
2008
Springer
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
182
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ATAL
2008
Springer
15 years 8 months ago
2008
Springer
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
171
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ATAL
2008
Springer
15 years 8 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 ...