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NIPS
2003
13 years 10 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
CLUSTER
2006
IEEE
14 years 2 months ago
A Simple Synchronous Distributed-Memory Algorithm for the HPCC RandomAccess Benchmark
The RandomAccess benchmark as defined by the High Performance Computing Challenge (HPCC) tests the speed at which a machine can update the elements of a table spread across globa...
Steven J. Plimpton, Ron Brightwell, Courtenay Vaug...
ICDCS
2003
IEEE
14 years 2 months ago
Updates in Highly Unreliable, Replicated Peer-to-Peer Systems
This paper studies the problem of updates in decentralised and self-organising P2P systems in which peers have low online probabilities and only local knowledge. The update strate...
Anwitaman Datta, Manfred Hauswirth, Karl Aberer
GECCO
2003
Springer
14 years 2 months ago
Reinforcement Learning Estimation of Distribution Algorithm
Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions ...
Topon Kumar Paul, Hitoshi Iba
CEC
2008
IEEE
14 years 3 months ago
Asynchronous multiple objective particle swarm optimisation in unreliable distributed environments
Abstract— This paper examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone e...
Ian Scriven, David Ireland, Andrew Lewis, Sanaz Mo...