Bart G. W. Craenen

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Constraint handling is not straightforward in evolutionary algorithms (ea) since the usual search operators, mutation and recombination, are ‘blind’ to constraints. Nevertheless, the issue is highly relevant, for many challenging problems involve constraints. Over the last decade numerous eas for solving constraint satisfaction problems (csp) have been(More)
The NewTies project is implementing a simulation in which societies of agents are expected to develop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are intended to be analogous to those faced by early, simple,(More)
This study proposes a novel approach for the analysis of brain responses in the modality of ongoing EEG elicited by the naturalistic and continuous music stimulus. The 512-second long EEG data (recorded with 64 electrodes) are first decomposed into 64 components by independent component analysis (ICA) for each participant. Then, the spatial maps showing(More)
The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameters of the algorithm was performed to optimise the performance of the algorithm on a commonly used test-set. The performance of the STLEA was then compared to the best known evolutionary(More)
This paper introduces a hybrid Tabu Search Evolutionary Algorithm for solving the binary constraint satisfaction problem, called CTLEA. A continuation of an earlier introduced algorithm, called the STLEA, the CTLEA replaces the earlier compound label tabu list with a conflict tabu list. Extensive experimental fine-tuning of parameters was performed to(More)
Historical studies are frequently perceived to be characterised as clear narratives defined by a series of fixed events or actions. In reality, even where critical historic events may be identified, historic documentation frequently lacks corroborative detail that supports verifiable interpretation. Consequently, for many periods and areas of research,(More)
We study a selected group of hybrid EAs for solving CSPs, consisting of the best performing EAs from the literature. We investigate the contribution of the evolutionary component to their performance by comparing the hybrid EAs with their "de-evolutionarised" variants. The experiments show that "de-evolutionarising" can increase performance, in some cases(More)
Multi-Agent Systems (MAS) are increasingly used to solve larger and more complex problems. To provide the computational resources needed to do this, MAS are increasingly distributed over multiple computational platforms. Different approaches for distributing MAS have been proposed over the years. One problem remains central whichever approach is used: how(More)
As much as ubiquitous computing systems are already claimed to exist in the real world, further development of these systems still pose challenges to computer science that are still quite beyond the state of the art. Two challenges standout in particular: the complexity of next-generation ubiquitous computing systems, and their inherent scalability issues.(More)