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Jorge M. Pacheco
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Proceedings Papers
. alife2018, ALIFE 2018: The 2018 Conference on Artificial Life614-615, (July 23–27, 2018) 10.1162/isal_a_00112
Proceedings Papers
. alife2018, ALIFE 2018: The 2018 Conference on Artificial Life286-287, (July 23–27, 2018) 10.1162/isal_a_00057
Proceedings Papers
. alif2016, ALIFE 2016, the Fifteenth International Conference on the Synthesis and Simulation of Living Systems19, (July 4–6, 2016) 10.1162/978-0-262-33936-0-ch007
Abstract
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A long-standing and central problem in Physics is to understand how collective behavior results from a given two- or N- body fundamental interaction. Similarly, in a society, a central problem is to understand the link between individual social behavior and emergent collective phenomena (vaccination, epidemics, crowd behavior, diffusion of innovations, global governance, etc). Here I address this problem by letting individuals engage in pair-wise interactions by means of a well- defined social dilemma (a prisoners dilemma of cooperation). These individuals are embedded in a social network that is both complex and adaptive. Adaptation here allows individuals to manifest preferences and resolve conflicts of interest, reshaping the network accordingly. Exact Monte-Carlo simulations reveal the inadequacy of any of the tools developed to date to predict the co-evolutionary dynamics of the population at large. I will present and discuss in detail an adaptive-network-sensitive observable that is capable of predicting the collective, population-wide dynamics, given prior knowledge of the fundamental rules that govern the social interaction between 2 individuals in a social network. In this fundamental step towards linking individual behavior with population wide dynamics, I show that adaptive social networks act to change the collective game, from a 2-person game to a N-person game exhibiting a radically different co- evolutionary dynamics, associated with a concomitant fundamental transformation of the nature of the associated Nash equilibria.
Proceedings Papers
. alif2016, ALIFE 2016, the Fifteenth International Conference on the Synthesis and Simulation of Living Systems470-471, (July 4–6, 2016) 10.1162/978-0-262-33936-0-ch076
Abstract
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Indirect Reciprocity (IR) is possibly the most elaborated and cognitively demanding mechanism of cooperation discovered so far. It involves status and reputations and has been heralded as providing the biological basis of our morality. Most theoretical models employed to date have studied how IR can lead to the emergence and sustainability of cooperation in infinite populations. However, it is known that cooperation, norms, reciprocity and the art of managing reputations, are features that date back to primitive, small-scale societies, when interactions mostly occurred within tribes. In small populations, stochastic finite size effects are not only important, but may even render infinite populations analyses misleading. Thus, it remains an open question which norms prevail in small-scale societies and their influence in the evolutionary dynamics of IR. With the current extended abstract, we would like to offer a new analysis of this problem. In Santos et al. (2016) we show that population size strongly influences the merits of each social norm, while proposing a new formal tool to assess the evolutionary dynamics of reputation-based systems in finite populations. We show that a single social norm (Stern-Judging) emerges as the leading norm in small-scale societies. That simple norm dictates that only whoever cooperates with good individuals, and defects against bad ones, deserves a good reputation.
Proceedings Papers
. ecal2015, ECAL 2015: the 13th European Conference on Artificial Life149, (July 20–24, 2015) 10.1162/978-0-262-33027-5-ch032
Proceedings Papers
. ecal2011, ECAL 2011: The 11th European Conference on Artificial Life108, (August 8–12, 2011) 10.7551/978-0-262-29714-1-ch108
Proceedings Papers
. ecal2011, ECAL 2011: The 11th European Conference on Artificial Life93, (August 8–12, 2011) 10.7551/978-0-262-29714-1-ch093