33 search results - page 6 / 7 » Iterative learning control with initial rectifying action |
IROS
2007
IEEE
15 years 3 months ago
2007
IEEE
— This paper presents an algorithm for adapting periodic behavior to gradual shifts in task parameters. Since learning optimal control in high dimensional domains is subject to t...
ICRA
2007
IEEE
15 years 3 months ago
2007
IEEE
— Ubiquitous robots need the ability to adapt their behaviour to the changing situations and demands they will encounter during their lifetimes. In particular, non-technical user...
ATAL
2007
Springer
15 years 3 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...
IJCAI
2001
14 years 11 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
81
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AAAI
2000
14 years 11 months ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...