1236 search results - page 178 / 248 » Opposition-Based Reinforcement Learning |
138
Voted
SMC
2007
IEEE
15 years 10 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...
150
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IROS
2006
IEEE
15 years 10 months ago
2006
IEEE
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
155
Voted
ECML
2005
Springer
15 years 9 months ago
2005
Springer
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
121
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ATAL
2008
Springer
15 years 6 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 ...
141
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AAAI
2006
15 years 5 months ago
2006
In this paper we propose a model for human learning and decision making in environments of repeated Cliff-Edge (CE) interactions. In CE environments, which include common daily in...