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» Using Learning in a Control Agent
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ATAL
2006
Springer
15 years 5 months ago
Probabilistic policy reuse in a reinforcement learning agent
We contribute Policy Reuse as a technique to improve a reinforcement learning agent with guidance from past learned similar policies. Our method relies on using the past policies ...
Fernando Fernández, Manuela M. Veloso
IAT
2008
IEEE
15 years 2 months ago
Scaling Up Multi-agent Reinforcement Learning in Complex Domains
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
Dan Xiao, Ah-Hwee Tan
ESANN
2004
15 years 3 months ago
A sliding mode controller using neural networks for robot manipulator
Abstract. This paper proposes a new sliding mode controller using neural networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compens...
Hajoon Lee, Dongkyung Nam, Cheol Hoon Park
EWRL
2008
15 years 3 months ago
Markov Decision Processes with Arbitrary Reward Processes
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
Jia Yuan Yu, Shie Mannor, Nahum Shimkin
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ATAL
2008
Springer
15 years 4 months ago
Identifying beneficial teammates using multi-dimensional trust
Multi-agent teams must be capable of selecting the most beneficial teammates for different situations. Multi-dimensional trustworthiness assessments have been shown significantly ...
Jaesuk Ahn, Xin Sui, David DeAngelis, K. Suzanne B...