We present in this paper a hybrid planning system which combines constraint satisfaction techniques and planning heuristics to produce optimal sequential plans. It integrates its ...
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...
Traditionally, Predator-Prey Models--although providing a more nature-oriented approach to multi-objective optimization than many other standard Evolutionary Multi-Objective Algori...
Christian Grimme, Joachim Lepping, Alexander Papas...
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
This research investigates the cognitive strategies and eye movements that people use to search for a known item in a hierarchical computer display. Computational cognitive models...