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195
Voted
CIMCA
2008
IEEE
16 years 25 days ago
Tree Exploration for Bayesian RL Exploration
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Christos Dimitrakakis
165
Voted
ATAL
2009
Springer
16 years 29 days ago
Abstraction in model checking multi-agent systems
ion in model checking multi-agent systems Mika Cohen Department of Computing Imperial College London London, UK Mads Dam Access Linnaeus Center Royal Institute of Technology Stockh...
Mika Cohen, Mads Dam, Alessio Lomuscio, Francesco ...
162
Voted
ATAL
2007
Springer
16 years 17 days ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
179
Voted
ATAL
2007
Springer
16 years 17 days ago
A complete distributed constraint optimization method for non-traditional pseudotree arrangements
Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multi-agent systems. Several current algorithms that solve general DCOP instan...
James Atlas, Keith Decker
193
Voted
PPOPP
2006
ACM
16 years 10 days ago
On-line automated performance diagnosis on thousands of processes
Performance analysis tools are critical for the effective use of large parallel computing resources, but existing tools have failed to address three problems that limit their scal...
Philip C. Roth, Barton P. Miller