Titlebook: Highlights on Practical Applications of Agents and Multi-Agent Systems; 10th International C Javier Bajo Pérez,Miguel A. Sánchez,Vicente Ju

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Roussanka Loukanova,M. Dolores Jiménez-Lópezosing the optimal control parameters of DE is a time-consuming task because they are problem depended. DE may have a strong ability in exploring the search space and locating the promising area of global optimum but may be slow at exploitation. Thus, in this paper, we propose a Gaussian Cauchy diffe

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Joel Azzopardi,Christopher Staffhms in large scale graph computing. The high time complexity, which even exceed that of the final algorithms occasionally, is the main factor to prevent their applicabilities. Existing graph partitioning algorithms are mostly based on multilevel k-way scheme or iterative label propagation. Most of t

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A. Gil,S. Rodríguez,F. De la Prieta,B. Martín,M. Morenointelligence (AGI) in game playing. However, deep learning is resource-intensive and the theory is not yet well developed. For small games, simple classical table-based Q-learning might still be the algorithm of choice. General Game Playing (GGP) provides a good testbed for reinforcement learning to

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Marta Fernandes,Constantino Martins,Luiz Faria,Paulo Couto,Cristiano Valente,Cristina Bastos,Fátima the dataset. Numerous algorithms use discretization of numerical data in their detection processes. This study investigates the effect of the employed discretization method on the unsupervised detection of each of the six anomaly types acknowledged in a recent typology of data anomalies. To this en