A very undesirable behavior of any heuristic algorithm is to be stuck in some specific parts of the search space, in particular in the basins of attraction of the local optima. Wh...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
Systems supporting situation awareness in large-scale control systems, such as, e. g., encountered in the domain of road traffic management, pursue the vision of allowing human ope...
Norbert Baumgartner, Wolfgang Gottesheim, Stefan M...
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Search spaces sampled by the process of Genetic Programming often consist of programs which can represent a function in many different ways. Thus, when the space is examined it i...
This paper studies the following question: given an instance of the propositional satisfiability problem, a randomized satisfiability solver, and a cluster of n computers, what i...
A new reduction on the size of the search space for cocyclic Hadamard matrices over dihedral groups D4t is described, in terms of the so called central distribution. This new searc...
—In recent years, there has been a move toward supporting the human element of Web search beyond a simple query box and a ranked list of search results. In this paper, we present...
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
— Hyper-heuristics or “heuristics to chose heuristics” are an emergent search methodology that seeks to automate the process of selecting or combining simpler heuristics in o...
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid