509 search results - page 11 / 102 » Compositional Models for Reinforcement Learning |
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
EACL
2006
ACL Anthology
13 years 9 months ago
2006
ACL Anthology
Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of automatically learning ...
AAAI
2010
13 years 9 months ago
2010
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
IAT
2010
IEEE
13 years 5 months ago
2010
IEEE
Abstract--The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...