LEADER 03696nam 22005775 450 001 9910484405103321 005 20200703060419.0 010 $a3-319-91542-8 024 7 $a10.1007/978-3-319-91542-5 035 $a(CKB)4100000004822022 035 $a(DE-He213)978-3-319-91542-5 035 $a(MiAaPQ)EBC5402147 035 $z(PPN)258865970 035 $a(PPN)227402952 035 $a(EXLCZ)994100000004822022 100 $a20180525d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBehaviourism in Studying Swarms: Logical Models of Sensing and Motoring /$fby Andrew Schumann 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XI, 468 p. 117 illus., 25 illus. in color.) 225 1 $aEmergence, Complexity and Computation,$x2194-7287 ;$v33 311 $a3-319-91541-X 327 $aIntroduction -- Actin Filament Networks -- Unconventional Computers Designed on Swarm Behaviours -- Conventional and Unconventional Automata on Swarm Behaviours -- Non-Archimedean Valued Fuzzy and Probability Logics -- Individual-Collective Duality in Swarm Behaviours -- Syllogistic Systems of Swarm Propagation -- Context-Based Games of Swarms. 330 $aThis book presents fundamental theoretical results for designing object-oriented programming languages for controlling swarms. It studies the logics of swarm behaviours. According to behaviourism, all behaviours can be controlled or even managed by stimuli in the environment: attractants (motivational reinforcement) and repellents (motivational punishment). At the same time, there are two main stages in reactions to stimuli: sensing (perceiving signals) and motoring (appropriate direct reactions to signals). This book examines the strict limits of behaviourism the point of view of symbolic logic and algebraic mathematics: how far can animal behaviours be controlled by the topology of stimuli? On the one hand, we can try to design reversible logic gates in which the number of inputs is the same as the number of outputs. In the authors? case, the behaviouristic stimuli are inputs in swarm computing and appropriate reactions at the motoring stage are its outputs. On the other hand, the problem is that even at the sensing stage each unicellular organism can be regarded as a logic gate in which the number of outputs (means of perceiving signals) greatly exceeds the number of inputs (signals). . 410 0$aEmergence, Complexity and Computation,$x2194-7287 ;$v33 606 $aComputational intelligence 606 $aComputational complexity 606 $aArtificial intelligence 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aComputational intelligence. 615 0$aComputational complexity. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aComplexity. 615 24$aArtificial Intelligence. 676 $a006.38 700 $aSchumann$b Andrew$4aut$4http://id.loc.gov/vocabulary/relators/aut$01091401 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484405103321 996 $aBehaviourism in Studying Swarms: Logical Models of Sensing and Motoring$92848385 997 $aUNINA