87 search results - page 14 / 18 » Direct Policy Search Reinforcement Learning for Robot Contro... |
88
Voted
AGENTS
1999
Springer
15 years 3 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
87
Voted
SMC
2007
IEEE
15 years 5 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...
ISCAS
2006
IEEE
15 years 5 months ago
2006
IEEE
— This paper describes a general approach for the unsupervised learning of behaviors in a behavior-based robot. The key idea is to formalize a behavior produced by a Motor Map dr...
ICANN
2010
Springer
15 years 21 days 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...
104
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ATAL
2007
Springer
15 years 5 months ago
2007
Springer
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...