139 search results - page 11 / 28 » Model-based function approximation in reinforcement learning |
PKDD
2009
Springer
15 years 6 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
80
Voted
AAAI
2008
15 years 2 months ago
2008
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
94
Voted
IROS
2006
IEEE
15 years 5 months ago
2006
IEEE
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
ICML
2003
IEEE
16 years 17 days ago
2003
IEEE
We consider incorporating action elimination procedures in reinforcement learning algorithms. We suggest a framework that is based on learning an upper and a lower estimates of th...
ICML
2010
IEEE
15 years 25 days ago
2010
IEEE
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...