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144
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ICML
2007
IEEE
16 years 2 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
GLOBECOM
2006
IEEE
15 years 8 months ago
Adaptive Learning of Transmission Control Policies for MIMO Fading Channels under Delay Constraint
— This paper addresses learning based adaptive resource allocation for wireless MIMO channels with Markovian fading. The problem is posed as Constrained Markov Decision Process w...
Dejan V. Djonin, Vikram Krishnamurthy
AAAI
2010
15 years 3 months ago
Symbolic Dynamic Programming for First-order POMDPs
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
Scott Sanner, Kristian Kersting
112
Voted
AAAI
2006
15 years 3 months ago
Incremental Least Squares Policy Iteration for POMDPs
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
Hui Li, Xuejun Liao, Lawrence Carin
GLOBECOM
2010
IEEE
14 years 12 months ago
Cooperation Stimulation in Cognitive Networks Using Indirect Reciprocity Game Modelling
In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their ow...
Yan Chen, K. J. Ray Liu