34 search results - page 5 / 7 » Towards Finite-Sample Convergence of Direct Reinforcement Le... |
137
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EUROCAST
2007
Springer
15 years 10 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
124
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AGENTS
1999
Springer
15 years 8 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
161
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PKDD
2009
Springer
15 years 8 months ago
2009
Springer
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
131
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FBIT
2007
IEEE
15 years 10 months ago
2007
IEEE
The paper describes our first experiments on Reinforcement Learning to steer a real robot car. The applied method, Neural Fitted Q Iteration (NFQ) is purely data-driven based on ...
154
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COGSR
2011
14 years 11 months ago
2011
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...