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» Reinforcement Learning for Operational Space Control
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NN
2010
Springer
125views Neural Networks» more  NN 2010»
13 years 5 months ago
Parameter-exploring policy gradients
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
Frank Sehnke, Christian Osendorfer, Thomas Rü...
AGENTS
2000
Springer
13 years 11 months ago
Adaptivity in agent-based routing for data networks
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems MAS's in noisy environme...
David Wolpert, Sergey Kirshner, Christopher J. Mer...
UAI
2008
13 years 8 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
AAAI
2008
13 years 9 months ago
Adaptive Management of Air Traffic Flow: A Multiagent Coordination Approach
This paper summarizes recent advances in the application of multiagent coordination algorithms to air traffic flow management. Indeed, air traffic flow management is one of the fu...
Kagan Tumer, Adrian K. Agogino
ISORC
2000
IEEE
13 years 11 months ago
Establishing a Data-Mining Environment for Wartime Event Prediction with an Object-Oriented Command and Control Database
This paper documents progress to date on a research project, the goal of which is wartime event prediction. The paper describes the operational concept, the datamining environment...
Marion G. Ceruti, S. Joe McCarthy