Principles in Noisy Optimization Applied to Multi-agent Coordination
Noisy optimization is a topic of growing interest for researchers working on mainstream optimization problems. Although several techniques for dealing with stochastic noise in optimization problems are covered in journals and conference proceedings, today
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Pratyusha Rakshit Amit Konar
Principles in Noisy Optimization Applied to Multi-agent Coordination
Cognitive Intelligence and Robotics Series editors Amit Konar, Department of Electronics and Tele-Communication Engineering, Jadavpur University, Kolkata, India Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
Cognitive Intelligence refers to the natural intelligence of humans/animals involving the brain to serve the necessary biological functioning to perform an intelligent activity. Although tracing a hard boundary to distinguish intelligent activities from others remains controversial, most of the common behaviors/activities of living organisms that cannot be fully synthesized by artificial means are regarded as intelligent. Thus the act of natural sensing and perception, understanding of the environment and voluntary control of muscles, blood-flow rate, respiration rate, heartbeat, and sweating rate, which can be performed by lower level mammals, indeed, are intelligent. Besides the above, advanced mammals can perform more sophisticated cognitive tasks, including logical reasoning, learning and recognition and complex planning/coordination, none of which could be realized artificially to the level of a baby, and thus are regarded as cognitively intelligent. The series aims at covering two important aspects of the brain science. First, it would attempt to uncover the mystery behind the biological basis of cognition with special emphasis on the decoding of stimulated brain signals/images. The coverage in this area includes neural basis of sensory perception, motor control, sensory-motor coordination and also understanding the biological basis of higher-level cognition, such as memory and learning, reasoning and complex planning. The second objective of the series is to publish brain-inspired models of learning, perception, memory and coordination for realization on robots to enable them to mimic the cognitive activities performed by the living creatures. These brain-inspired models of machine intelligence would supplement the behavioral counterparts, studied in traditional AI. The series includes textbooks, monographs, contributed volumes and even selected conference proceedings.
More information about this series at http://www.springer.com/series/15488
Pratyusha Rakshit Amit Konar •
Principles in Noisy Optimization Applied to Multi-agent Coordination
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Pratyusha Rakshit Department of Electronics and Telecommunication Engineering Jadavpur University Kolkata, West Bengal, India
Amit Konar Department of Electronics and Telecommunication Engineering Jadavpur University Kolkata, West Bengal, India
ISSN 2520-1956 ISSN 2520-1964 (electronic) Cognitive Intelligence and Robotics ISBN 978-981-10-8641-0 ISBN 978-981-10-8642-7 (eBook) https://doi.org/10.1007/978-981-10-8642-7 Library of Congress Control Number: 2018952870 © Springer Nature Singapore Pte Ltd. 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the wh
