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TSMC
2008
146views more  TSMC 2008»
15 years 6 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ICRA
2010
IEEE
136views Robotics» more  ICRA 2010»
15 years 4 months ago
Efficient planning under uncertainty for a target-tracking micro-aerial vehicle
A helicopter agent has to plan trajectories to track multiple ground targets from the air. The agent has partial information of each target's pose, and must reason about its u...
Ruijie He, Abraham Bachrach, Nicholas Roy
ATAL
2011
Springer
14 years 6 months ago
Maximum causal entropy correlated equilibria for Markov games
Motivated by a machine learning perspective—that gametheoretic equilibria constraints should serve as guidelines for predicting agents’ strategies, we introduce maximum causal...
Brian D. Ziebart, J. Andrew Bagnell, Anind K. Dey
CCGRID
2003
IEEE
15 years 12 months ago
Scheduling Distributed Applications: the SimGrid Simulation Framework
— Since the advent of distributed computer systems an active field of research has been the investigation of scheduling strategies for parallel applications. The common approach...
Arnaud Legrand, Loris Marchal, Henri Casanova
ICPP
2005
IEEE
16 years 5 days ago
Service Migration in Distributed Virtual Machines for Adaptive Grid Computing
Computational grids can integrate geographically distributed resources into a seamless environment. To facilitate managing these heterogenous resources, the virtual machine gy pro...
Song Fu, Cheng-Zhong Xu