Most of us must have been fascinated by the eye catching displays of collectively moving animals. Schools of fish can move in a rather orderly fashion and then change direction amazingly abruptly. There are a huge number of further examples both from the living and the non-living world for phenomena during which the many interacting, permanently moving units seem to arrive at a common behavioural pattern taking place in a short time. As a paradigm of this type of phenomena we consider the problem of how birds arrive at a decision resulting in their synchronized landing. We introduce a simple model to interpret this process. Collective motion prior to landing is modelled using a simple self-propelled particle (SPP) system with a new kind of boundary condition, while the tendency and the sudden propagation of the intention of landing is introduced through rules analogous to the random field Ising model in an external field. We show that our approach is capable of capturing the most relevant features of collective decision making in a system of units with a variance of individual intentions and being under an increasing level of pressure to switch states. We find that as a function of the few parameters of our model the collective switching from the flying to the landing state is indeed much sharper than the distribution of the individual landing intentions. The transition is accompanied by a number of interesting features discussed in this report.
Learning to flock in open space by avoiding collisions and staying together
Universitá degli Studi dell’Insubria（因苏布里亚大学）；I.N.F.N. Sezione di Milano（意大利国家核物理研究所米兰分部）；The Abdus Salam International Center for Theoretical Physics (ICTP)（阿卜杜勒·萨拉姆国际理论物理中心）；Department of Oncology, Università degli Studi di Torino（米兰大学）；Universitá degli Studi di Milano
Threat Evasion and Information Propagation in Cognitive Flocks
Theoretical Physics of Living Matter, Institute for Advanced Simulation, Forschungszentrum Jülich（尤利希研究中心先进模拟研究所活体物质理论物理）；University of British Columbia（不列颠哥伦比亚大学）
Flocking and turning: a new model for self-organized collective motion
a Istituto Sistemi Complessi (ISC--CNR), Via dei Taurini 19, 00185 Roma, Italy b Dipartimento di Fisica, ``Sapienza'' Universit\'a di Roma, P.le Aldo Moro 2, 00185 Roma, Italy c Initiative for the Theoretical Sciences, The Graduate Center, 365 Fifth Avenue, New York, NY 10016 USA d Instituto de Investigaciones Fisicoqu \' micas Te \'o ricas y Aplicadas (INIFTA)；Departamento de F \' sica, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, c.c. 16, suc. 4, 1900 La Plata, Argentina e CONICET La Plata, Consejo Nacional de Investigaciones Cient \' ficas y T \'e cnicas, Argentina f Laboratoire de Physique Statistique de l' \' E cole Normale Sup\'erieure, CNRS；h Laboratoire de Physique Th\'eorique de l'\'Ecole Normale Sup\'erieure, CNRS；University Paris VI, 24 rue Lhomond, 75231 Paris Cedex 05, France
