Chapter 8 Social things / Social outcome

Conflicts of interest

Altruism

Influence and culture

Flocks / Herds of clever guys

Economic universalities / universality

Referencias y comentarios:

· Dos referencias generales para este capítulo son el libro de J. Marro con R. Dickman, que define y describe el comportamiento de otros modelos de interés social y detalles adicionales de modelos discutidos o mencionados en FyV, que ya ha sido referenciado en el capítulo 1, y el libro Modeling Cooperative Behavior in the Social Sciences, editado por Pedro Garrido, Joaquín Marro y Miguel A. Muñoz en American Institute of Physics, Nueva York 2005, también referenciado anteriormente.

· El dilema del prisionero se desarrolla con generosidad en plato.stanford.edu (véase también es.wikipedia.org) y hay juegos interactivos en www.princeton.edu y prisonersdilemma.groenefee.nl.

· In “The arithmetic of mutual help”, Scientific American 272, 76 (1995), Martin A. Nowak, Robert M. May, and Karl Sigmund describe applications to socio-biology of the prisoner’s dilemma; see also the web sites plato.stanford.edu/entries/ prisoner-dilemma/ and prisonersdilemma.groenefee.nl/. For some related models, see Modeling cooperative behavior in the social sciences, edited by Pedro L. Garrido, J. Marro and Miguel A. Muñoz (American Institute of Physics, New York 2005). For recent extensions, see “Effects of punishment in a mobile population playing the prisoner’s dilemma game”, by Daniel R. Amor and Joaquim Fort, Physical Review E 84, 066115 (2011). General references to this chapter are also Game theory: A non-technical introduction, by Morton D. Davis (Dover, New York 1997), Evolutionary dynamics: Exploring the equations of life, by Martin Nowak (Belknap Press, Cambridge MA 2006), The evolution of cooperation, by Robert Axelrod (Basic Books, New York 2006); see also further references by Mark Newman in American Journal of Physics 79, 800 (2011).

· See “Reversible Ratchets as Brownian Particles in Adiabatically Changing Periodic Potential”, Physical Review E 57, 7297 (1998), J.M.R. Parrondo, and discussion by Gregory P. Harmer and Derek Abbott in “Game theory: Losing strategies can win by Parrondo’s paradox”, Nature 402, 864 (1999).

· Garrett Hardin’s “The Tragedy of the Commons”, Science 162, 1243 (1968) and “Extensions”, Science 280, 682 (1998). See www.garretthardinsociety.org.

· Para modelos de agentes, un clásico es “Dynamic models of segregation”, by Thomas C. Schelling in Journal of Mathematical Sociology 1, 143 (1971), que trata de segregación racial.

· On the origins of altruism toward one’s own social group, see "Did warfare among ancestral hunter-gatherers affect the evolution of human social behaviors?", by Samuel Bowles, Science 324, 1293 (2009). Es interesante notar a este respecto que un estudio reciente —“Altruistic Wasps?” by Raghavendra Gadagkar in Science 12, 833 (2011), and details in “Nest inheritance is the missing source of direct fitness in a primitively eusocial insect”, by Ellouise Leadbeater et al., Science 12, 874 (2011)— sugiere que algunos casos de cooperación aparentemente altruista en la naturaleza tienen una motivación egoísta. Es el caso of wasps Polistes dominulus que, aunque se creía que colaboraban y estaban al servicio de su reina con objeto de beneficiar a sus familiares, en realidad lo hacen en beneficio propio y para tener la oportunidad de heredar el trono de la reina a su muerte.

· Martin A. Nowak, Evolutionary Dynamics: Exploring the Equations of Life (Harvard University Press, 2006).

· Para un compendio de algunas técnicas sobre modelos de agentes y similares puede verse el libro Nonequilibrium Phase Transitions in Lattice Systems, Joaquín Marro and Ronald Dickman (Cambridge University Press, 2005), que también describe modelos básicos introducidos en este capítulo y en otras partes del curso.

· Recomendamos el libro de Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration (Princeton University Press 1997). El modelo que describimos en una red, que modifica al de Axelrod, ha sido propuesto en “Nonequilibrium phase transition in the coevolution of networks and opinions”, Petter Holme and Mark E.J. Newman, Physical Review E 74, 056108 (2006).

· El modelo de Axelrod ha sido también estudiado en “Nonequilibrium Phase Transition in a Model for Social Influence”, por Claudio Castellano, Matteo Marsili y Alessandro Vespignani, en Physical Review Letters 85, 3536 (2000).

· On the emergence of cultural complexity, see "Late Pleistocene demography and the appearance of modern human behavior, Adam Powell, Stephen Shennan, and Mark G.Thomas, Science 324, 1298 (2009)

· En relación con economía y finanzas, general bibliography is: The economy as an evolving complex system, Philip W. Anderson, Kenneth J. Arrow and David Pines (Addison-Wesley, Redwood 1988); An Introduction to Econophysics —Correlations and Complexity in Finance, Rosario N. Mantegna and H. Eugene Stanley (Cambridge University Press 2000); The Statistical Mechanics of Financial Markets, Johannes Voit (Springer-Verlag, Berlin 2001); Why Stock Markets Crash: Critical Events in Complex Financial Systems, Didier Sornette (Princeton University Press 2002); “Is Economics the Next Physical Science?”, Physics Today, September 2005, page 37. Una sencilla perspectiva de la econofísica en el contexto de la teoría económica tradicional puede también verse en www.physicstoday.org.

· Recordamos ahora el libro de N.N. Taleb, “The black swan”, mencionado en el capítulo 5.

· El modelo de comportamiento gregario se propone en “Transmission of information and herd behaviour: an application to financial markets”, Physical Review Letters 85, 5659 (2000), Víctor M. Eguíluz and Martin G. Zimmermann.

· También recomendamos en este contexto: S. Ghashghaie, W. Breymann, J. Peinke, P. Talkner y Y. Dodge en Nature 381, 767 (1996); eil.stanford.edu; “Scale invariance and universality of economic fluctuations”, por H.E. Stanley, L.A.N. Amaral, P. Gopikrishnan y V. Plerou, en Physica A 283, 31 (2000); y “Scale invariance and universality in economic phenomena”, de H.E. Stanley, L.A.N. Amaral, P. Gopikrishnan, V. Plerou y M.A. Salinger, en Journal of Physics: Condensed Matter 14, 2121 (2002).

· “Dynamics of crowd disasters: An empirical study”, Dirk Helbing, Anders Johansson and Habib Z. Al-Abideen, Physical Review E 75, 046109 (2007). For computer models treating people as decision-makers rather than passive particles with attractive and repulsive forces, see "How simple rules determine pedestrian behavior and crowd disasters" Mehdi Moussaïda, Dirk Helbingb, and Guy Theraulaza, PNAS 108, 6884 (2011). X.L. Zhang, W.G. Weng, and H.Y. Yuan studied in “Empirical study of crowd behavior during a real mass event”, Journal of Statistical Mechanics: Theory and Experiment P08012 (2012) the case of many people going through a door and then passing a bridge by means of a visualization algorithm used in fluid experiments to show two movement phases, namely, laminar flow on the bridge and stop-and-go waves in the bottleneck area.

· On how physics is bringing new ideas and methodologies to the study of economics, see An introduction to econophysics: Correlations and complexity in finance, By Rosario N. Mantegna and E. Eugene Stanley (Cambridge Univ. Press, Cambridge 1999), Why stock markets crash: Critical events in complex financial systems, by Didier Sornette (Princeton Univ. Press, Princeton 2004), “Is economics the next physical science” by J. Doyne Farmer, Martin Shubik, and Eric Smith, Physics Today 58, 37 (2005), and the recent comments “Econophysics and the Current Economic Turmoil” by H. Eugene Stanley, in APS News 17, No. 11, page 8 (December 2008) and “The (unfortunate) complexity of economy” by Jean-Philippe Bouchaud in Physics World 28 (April 2009).

· For some steps towards theory in this context, see also S. Ghashghaie, W. Breymann, J. Peinke, P. Talkner and Y. Dodge, Nature 381, 767 (1996); “Scale invariance and universality in economic phenomena”, H.Eugene Stanley, et al., Journal of Physics: Condensed Matter 14, 2121 (2002); “Agent-based models of financial markets”, Egle Samanidou, Elmar Zschischang, Dietrich Stauffer and Thomas Lux, Reports on Progress in Physics 70, 409 (2007).

· “Limits of predictability in human mobility”, Chaoming Song, Zehui Qu, Nicholas Blumm and Albert-László Barabási, Science 327, 1018 (2010), which studies the role of randomness in human behavior and to what degree are individual human actions predictable.

Nota: véanse las referencias y enlaces que se incluyen en las dispositivas del curso, que a menudo completan las anteriores.