473 search results - page 32 / 95 » Optimal policy switching algorithms for reinforcement learni... |
TSMC
2008
14 years 11 months ago
2008
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
163
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ICAART
2010
INSTICC
15 years 9 months ago
2010
INSTICC
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
ECML
2006
Springer
15 years 3 months ago
2006
Springer
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
SBIA
2004
Springer
15 years 5 months ago
2004
Springer
This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
206
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Publication
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...