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» Gaussian Processes in Reinforcement Learning
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ICML
1994
IEEE
15 years 1 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
IJRR
2008
151views more  IJRR 2008»
14 years 9 months ago
Trajectory Optimization using Reinforcement Learning for Map Exploration
Automatically building maps from sensor data is a necessary and fundamental skill for mobile robots; as a result, considerable research attention has focused on the technical chall...
Thomas Kollar, Nicholas Roy
EURONGI
2005
Springer
15 years 3 months ago
An Afterstates Reinforcement Learning Approach to Optimize Admission Control in Mobile Cellular Networks
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
José Manuel Giménez-Guzmán, J...
EACL
2006
ACL Anthology
14 years 11 months ago
Using Reinforcement Learning to Build a Better Model of Dialogue State
Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of automatically learning ...
Joel R. Tetreault, Diane J. Litman
JSW
2007
112views more  JSW 2007»
14 years 9 months ago
The Challenge of Training New Architects: an Ontological and Reinforcement-Learning Methodology
— This paper describes the importance of new skilled architects in the discipline of Software and Enterprise Architecture. Architects are often idealized as super heroes with a l...
Anabel Fraga, Juan Lloréns