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» Benchmarking and solving dynamic constrained problems
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INFOCOM
2008
IEEE
15 years 4 months ago
A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks
Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed alg...
Yi Shi, Y. Thomas Hou
ATAL
2007
Springer
15 years 3 months 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
CP
2005
Springer
15 years 3 months ago
Neighbourhood Clause Weight Redistribution in Local Search for SAT
Abstract. In recent years, dynamic local search (DLS) clause weighting algorithms have emerged as the local search state-of-the-art for solving propositional satisfiability proble...
Abdelraouf Ishtaiwi, John Thornton, Abdul Sattar, ...
AIPS
2008
14 years 12 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan
101
Voted
JAIR
2008
126views more  JAIR 2008»
14 years 9 months ago
Optimal and Approximate Q-value Functions for Decentralized POMDPs
Decision-theoretic planning is a popular approach to sequential decision making problems, because it treats uncertainty in sensing and acting in a principled way. In single-agent ...
Frans A. Oliehoek, Matthijs T. J. Spaan, Nikos A. ...