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» Using Learning in a Control Agent
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ATAL
2006
Springer
13 years 11 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
13 years 8 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
13 years 9 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
13 years 9 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
ATAL
2008
Springer
13 years 10 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...