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Computational complexity. --- Complexity, Computational --- Electronic data processing --- Machine theory

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Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems.

Computers / Artificial Intelligence --- Computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace

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Over two parts, this book examines the meaning of complexity in the context of systems both social and natural. Chapters cover such topics as the traveling salesman problem, models of opinion dynamics creation, a universal theory for knowledge formation in children, the evaluation of landscape organization and dynamics through information entropy indicators, and studying the performance of wind farms using artificial neural networks. We hope that this book will be useful to an audience interested in the different problems and approaches that are used within the theory of complexity.

Computational complexity. --- NP-complete problems.

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Nature evolves mainly in a statistical way. Different strategies, formulas, and conformations are continuously confronted in the natural processes. Some of them are selected and then the evolution continues with a new loop of confrontation for the next generation of phenomena and living beings. Failings are corrected without a previous program or design. The new options generated by different statistical and random scenarios lead to solutions for surviving the present conditions. This is the general panorama for all scrutiny levels of the life cycles. Over three sections, this book examines different statistical questions and techniques in the context of machine learning and clustering methods, the frailty models used in survival analysis, and other studies of statistics applied to diverse problems.

Statistics --- Mathematical statistics --- Data processing.

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Over two parts, this book examines the meaning of complexity in the context of systems both social and natural. Chapters cover such topics as the traveling salesman problem, models of opinion dynamics creation, a universal theory for knowledge formation in children, the evaluation of landscape organization and dynamics through information entropy indicators, and studying the performance of wind farms using artificial neural networks. We hope that this book will be useful to an audience interested in the different problems and approaches that are used within the theory of complexity.

Computational complexity. --- NP-complete problems.