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Titlebook: Behaviourism in Studying Swarms: Logical Models of Sensing and Motoring; Andrew Schumann Book 2019 Springer International Publishing AG, p

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期刊全稱Behaviourism in Studying Swarms: Logical Models of Sensing and Motoring
影響因子2023Andrew Schumann
視頻videohttp://file.papertrans.cn/183/182925/182925.mp4
發(fā)行地址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
學科分類Emergence, Complexity and Computation
圖書封面Titlebook: Behaviourism in Studying Swarms: Logical Models of Sensing and Motoring;  Andrew Schumann Book 2019 Springer International Publishing AG, p
影響因子.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 (signa
Pindex Book 2019
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978-3-030-08271-0Springer International Publishing AG, part of Springer Nature 2019
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Daniel Deronda and Circumcision,tions with two quantifiers: ‘all neighbours of an attractant/repellent’ and ‘some neighbours of an attractant/repellent’. In this chapter, I examine Aristotelian and non-Aristotelian syllogistics for simulating the swarms. In the Aristotelian syllogistic the models verifying swarming are well-founde
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