Overview
- Presents fundamental theoretical results for designing object-oriented programming languages for controlling swarms
- Studies the logics of swarm behaviours
- Proposes various logical tools for analyzing swarm reactions to attractants and repellents: non-classical logics, non-Archimedean probability theory, and bio-inspired game theory
Part of the book series: Emergence, Complexity and Computation (ECC, volume 33)
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Table of contents (13 chapters)
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Front Matter
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Back Matter
Keywords
- Swarm Computing
- Swarm Intelligence
- Swarm Behaviour
- Social Behaviour
- Reflexive Games
- Behaviourism
- Analogic Computing
- Reaction-Diffusion Computing
- Complex Systems
- Multiagent Systems
- Cellular Automata
- Artificial Life
- Emergence
- Agent Based Computation
- Non-Classical Logics
- Fuzzy Logics, Many-Valued Logics
- Bio-Inspired Game Theory, Actin Filament Networks
- Trichobilharzia Szidati, Schistosomatidae
- Amoeba Proteus
- Physarum Polycephalum, Slime Mould
About this book
This book presents fundamental theoretical results for designing object-oriented programming languages for controlling swarms. It studies the logics of swarm behaviours. According to behaviourism, all behaviours can be controlled or even managed by stimuli in the environment: attractants (motivational reinforcement) and repellents (motivational punishment). At the same time, there are two main stages in reactions to stimuli: sensing (perceiving signals) and motoring (appropriate direct reactions to signals). This book examines the strict limits of behaviourism from the point of view of symbolic logic and algebraic mathematics: how far can animal behaviours be controlled by the topology of stimuli? On the one hand, we can try to design reversible logic gates in which the number of inputs is the same as the number of outputs. In this case, the behaviouristic stimuli are inputs in swarm computing and appropriate reactions at the motoring stage are its outputs. On the other hand, the problem is that even at the sensing stage each unicellular organism can be regarded as a logic gate in which the number of outputs (means of perceiving signals) greatly exceeds the number of inputs (signals).
Authors and Affiliations
Bibliographic Information
Book Title: Behaviourism in Studying Swarms: Logical Models of Sensing and Motoring
Authors: Andrew Schumann
Series Title: Emergence, Complexity and Computation
DOI: https://doi.org/10.1007/978-3-319-91542-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2019
Hardcover ISBN: 978-3-319-91541-8Published: 06 June 2018
Softcover ISBN: 978-3-030-08271-0Published: 14 February 2019
eBook ISBN: 978-3-319-91542-5Published: 25 May 2018
Series ISSN: 2194-7287
Series E-ISSN: 2194-7295
Edition Number: 1
Number of Pages: XI, 468
Number of Illustrations: 92 b/w illustrations, 25 illustrations in colour
Topics: Computational Intelligence, Complexity, Artificial Intelligence