509 search results - page 66 / 102 » Using Learning for Approximation in Stochastic Processes |
115
Voted
IROS
2008
IEEE
15 years 8 months ago
2008
IEEE
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
147
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IWLCS
2005
Springer
15 years 7 months ago
2005
Springer
Aiming to clarify the convergence or divergence conditions for Learning Classifier System (LCS), this paper explores: (1) an extreme condition where the reinforcement process of ...
126
Voted
ML
2006
ACM
15 years 2 months ago
2006
ACM
Most game programs have a large number of parameters that are crucial for their performance. While tuning these parameters by hand is rather difficult, efficient and easy to use ge...
149
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ICASSP
2011
IEEE
14 years 6 months ago
2011
IEEE
Correlated equilibria are a generalization of Nash equilibria that permit agents to act in a correlated manner and can therefore, model learning in games. In this paper we define...
128
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ATAL
2009
Springer
15 years 9 months ago
2009
Springer
This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these pr...