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GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 3 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...
HPCC
2007
Springer
14 years 3 months ago
A Complex Network-Based Approach for Job Scheduling in Grid Environments
Many optimization techniques have been adopted for efficient job scheduling in grid computing, such as: genetic algorithms, simulated annealing and stochastic methods. Such techni...
Renato Porfirio Ishii, Rodrigo Fernandes de Mello,...
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
14 years 3 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
CGI
2006
IEEE
14 years 3 months ago
Quasi-physical Simulation of Large-Scale Dynamic Forest Scenes
This paper presents a quasi-physically based approach for interactively simulating large-scale dynamic forest scenes under different wind conditions. We introduce theories from th...
Long Zhang, Chengfang Song, Qifeng Tan, Wei Chen, ...
GLOBECOM
2006
IEEE
14 years 3 months ago
Multi-Stage Investment Decision under Contingent Demand for Networking Planning
Telecommunication companies, such as Internet and cellular service providers, are seeing rapid and uncertain growth of traffic routed through their networks. It has become a chall...
Miguel F. Anjos, Michael Desroches, Anwar Haque, O...