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» Agent Based Processing of Global Evaluation Function
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GECCO
2008
Springer
180views Optimization» more  GECCO 2008»
13 years 9 months ago
An agent-based collaborative evolutionary model for multimodal optimization
A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary Model (RACE) combining several evolutionary techniques with agent-based modeling ...
Rodica Ioana Lung, Camelia Chira, Dumitru Dumitres...
ISCAPDCS
2003
13 years 9 months ago
Utilization of Separate Caches to Eliminate Cache Pollution Caused by Memory Management Functions
Data intensive service functions such as memory allocation/de-allocation, data prefetching, and data relocation can pollute processor cache in conventional systems since the same ...
Mehran Rezaei, Krishna M. Kavi
DAGM
2003
Springer
14 years 1 months ago
A Generative Model Based Approach to Motion Segmentation
We address the question of how to choose between different likelihood functions for motion estimation. To this end, we formulate motion estimation as a problem of Bayesian inferen...
Daniel Cremers, Alan L. Yuille
TEC
2010
112views more  TEC 2010»
13 years 2 months ago
Population-Based Algorithm Portfolios for Numerical Optimization
In this paper, we consider the scenario that a population-based algorithm is applied to a numerical optimization problem and a solution needs to be presented within a given time bu...
Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 2 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone