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» Reinforcement Learning: An Introduction
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140
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SASO
2009
IEEE
15 years 10 months ago
Distributed W-Learning: Multi-Policy Optimization in Self-Organizing Systems
—Large-scale agent-based systems are required to self-optimize towards multiple, potentially conflicting, policies of varying spatial and temporal scope. As a result, not all ag...
Ivana Dusparic, Vinny Cahill
135
Voted
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
15 years 10 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
134
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IROS
2007
IEEE
172views Robotics» more  IROS 2007»
15 years 10 months ago
Motor control optimization of compliant one-legged locomotion in rough terrain
— While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for ada...
Fumiya Iida, Russ Tedrake
152
Voted
ICCS
2007
Springer
15 years 9 months ago
Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces
New architectures for Brain-Machine Interface communication and control use mixture models for expanding rehabilitation capabilities of disabled patients. Here we present and test ...
Jack DiGiovanna, Loris Marchal, Prapaporn Rattanat...
127
Voted
JSSPP
2007
Springer
15 years 9 months ago
A Self-optimized Job Scheduler for Heterogeneous Server Clusters
Heterogeneous clusters and grid infrastructures are becoming increasingly popular. In these computing infrastructures, machines have different resources, including memory sizes, d...
Elad Yom-Tov, Yariv Aridor