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ICML
2010
IEEE
13 years 9 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
13 years 11 months ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
HIS
2004
13 years 9 months ago
Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...
Karla Figueiredo, Marley B. R. Vellasco, Marco Aur...
AUSAI
2005
Springer
14 years 1 months ago
Adaptive Utility-Based Scheduling in Resource-Constrained Systems
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...
David Vengerov
IJSNET
2010
317views more  IJSNET 2010»
13 years 2 months ago
MRL-CC: a novel cooperative communication protocol for QoS provisioning in wireless sensor networks
: Cooperative communications have been demonstrated to be effective in combating the multiple fading effects in wireless networks, and improving the network performance in terms of...
Xuedong Liang, Min Chen, Yang Xiao, Ilangko Balasi...