Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
We describe techniques to optimally select landmarks for performing mobile robot localization by matching terrain maps. The method is based upon a maximum-likelihood robot localiza...
In this paper, we explore a hybrid global/local search optimization framework for dynamic voltage scaling in embedded multiprocessor systems. The problem is to find, for a multipr...
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...
DPOP is an algorithm for distributed constraint optimization which has, as main drawback, the exponential size of some of its messages. Recently, some algorithms for distributed c...