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» Reducing the complexity of multiagent reinforcement learning
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ICML
2007
IEEE
14 years 7 months ago
Reinforcement learning by reward-weighted regression for operational space control
Many robot control problems of practical importance, including operational space control, can be reformulated as immediate reward reinforcement learning problems. However, few of ...
Jan Peters, Stefan Schaal
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
14 years 1 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
AAAI
2000
13 years 8 months ago
Inter-Layer Learning Towards Emergent Cooperative Behavior
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even t...
Shawn Arseneau, Wei Sun, Changpeng Zhao, Jeremy R....
CIIA
2009
13 years 8 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
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