Cooperation is needed for evolution to construct new levels of organization. Genomes, cells, multicellular organisms, social insects, and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. For each mechanism, a simple rule is derived that specifies whether natural selection can lead to cooperation.
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"In this section, we extend the two-island competition algorithm (CICC) applied in    to a multi-island cooperative coevolution (MICCC) algorithm which enforces competition and collaboration between various different suboptimal decompositions that are implemented as islands. Since evolution is a unity of cooperation and opposition  , competition in a surrounding of limited resources is vital for survival. In competitive coevolution , the individual show its competitive ability through its fitness scores. "
[Show abstract][Hide abstract] ABSTRACT: Problem decomposition is an important attribute of cooperative coevolution that depends on the nature of the problems in terms of separability which is defined by the level of interaction amongst decision variables. Recent work in cooperative coevolution featured competition and collaboration of problem decomposition methods that was implemented as islands in a method known as competitive island cooperative coevolution (CICC). In this paper, a multi-island competitive cooperative coevolution (MICCC) is proposed in which several different problem decompositions are given a chance to compete, collaborate and motivate other islands while converging to a common solution. The performances of MICC using three and five island are evaluated on eight different benchmark functions and are compared with CICC where only two islands were utilized. The results from the experimental analysis show that competition and collaboration of several different island can yield solutions with a quality better than the two-island competition algorithm (CICC) on most complex multi-modal problems.
International Conference on Neural Information Processing (ICONIP), Istanbul, Turkey; 11/2015
"Mounting evidence shows that humans cooperate with non-kin even when doing so implies paying irrecoverable costs (Ledyard 1995, Gintis 2000, Henrich et al. 2001, Fehr & Gächter 2002, Bowles & Gintis 2003, Camerer 2003). These prosocial behaviors are inconsistent with the strict pursue of self-interest and thus constitute a challenge for disciplines ranging from evolutionary biology to the social and behavioral sciences (Nowak 2006, Fehr & Camerer 2007, Harbaugh et al. 2007, Perc & Szolnoki 2008, Roca et al. 2009, Capraro 2013, Exadaktylos et al. 2013, Rand & Nowak 2013, Gutiérrez-Roig et al. 2014, Raihani 2014). "
[Show abstract][Hide abstract] ABSTRACT: Even though human social behavior has received considerable scientific attention in the last decades, its cognitive underpinnings are still poorly understood. Applying a dual-process framework to the study of social preferences, we show in two studies that individuals with a more reflective/deliberative cognitive style, as measured by scores on the Cognitive Reflection Test (CRT), are more likely to make choices consistent with “mild” altruism in simple non-strategic decisions. Such choices increase social welfare by increasing the other person’s payoff at very low or no cost for the individual. The choices of less reflective individuals (i.e. those who rely more heavily on intuition), on the other hand, are more likely to be associated with either egalitarian or spiteful motives. We also identify a negative link between reflection and choices characterized by “strong” altruism, but this result holds only in Study 2. Moreover, we provide evidence that the relationship between social preferences and CRT scores is not driven by general intelligence. We discuss how our results can reconcile some previous conflicting findings on the cognitive basis of social behavior.
Frontiers in Behavioral Neuroscience 10/2015; forthcoming. · 3.27 Impact Factor
"By maximizing inclusive fitness, relatedness apparently enhances cooperation over resource management (Alvard 2003; Krupp et al. 2008). That kinship and territoriality were the foundations of cooperative societies before the evolution of the state is well researched (Engels and Morgan 1978; Eriksen 2004); unpacking the social and biological foundations of relatedness has shaped our understanding of the conditions under which cooperation thrives (Axelrod and Hamilton 1981; Nowak 2006). Biological kinship and alliances also provide critical insights into social organisation , prohibition and regulatory rules, property inheritance and ownership (Gough 1952; Carsten 2000). "
[Show abstract][Hide abstract] ABSTRACT: It has been suggested that kin groups are better predisposed to cooperatively manage essential natural resources than non-kin groups because of inclusive fitness gains. Whether these long-term genetic pay-offs sufficiently offset the immediate costs of cooperation in periods of scarcity is uncertain. We compared patterns of resource sharing across three island communities in the Nicobar Archipelago affected by the 2004 tsunami. While sharing mechanisms were similar across regions, group composition varied: Central and Southern Nicobar were organised along kinship lines, while Chowra was organised as corporate alliances of unrelated households. We documented post-tsunami losses and conflicts emerging in resource sharing after the event. While kin groups showed considerable breakdown in resource sharing arrangements , corporate communities in Chowra were much more resilient to change. Our results suggest that the more immediate reciprocity of corporate alliances may outweigh the potential benefits of inclusive fitness when faced with conditions of extreme resource scarcity.
Human Ecology 09/2015; DOI:10.1007/s10745-015-9778-5 · 1.63 Impact Factor