509 search results - page 44 / 102 » Using Learning for Approximation in Stochastic Processes |
116
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ML
2008
ACM
15 years 2 months ago
2008
ACM
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
116
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ATAL
2009
Springer
15 years 9 months ago
2009
Springer
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
135
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ICML
1996
IEEE
15 years 6 months ago
1996
IEEE
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
131
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CDC
2010
IEEE
14 years 9 months ago
2010
IEEE
We address the consensus-based distributed linear filtering problem, where a discrete time, linear stochastic process is observed by a network of sensors. We assume that the consen...
113
Voted
IJCAI
2007
15 years 3 months ago
2007
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...