62,401 research outputs found

    Modeling collective dynamics of social systems: Incorporating various social mechanisms into agent-based models

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    I present three original papers demonstrating complex behavior arising from collective dynamics in agent-based models (ABM) focusing on evolutionary and cognitive mechanisms. The first report demonstrates the coupled emergence of cooperation and selfish punishment behavior in groups of individuals playing an iterated public goods game. The second report demonstrates the effects of mental modeling within groups of decision makers. The third report demonstrates a synthesis of evolutionary and cognitive mechanisms

    Evolution of swarming behavior is shaped by how predators attack

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    Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group. Using an evolutionary model of a predator-prey system, we show that how predators attack is critical to the evolution of the selfish herd. Following this discovery, we show that density-dependent predation provides an abstraction of Hamilton's original formulation of ``domains of danger.'' Finally, we verify that density-dependent predation provides a sufficient selective advantage for prey to evolve the selfish herd in response to predation by coevolving predators. Thus, our work corroborates Hamilton's selfish herd hypothesis in a digital evolutionary model, refines the assumptions of the selfish herd hypothesis, and generalizes the domain of danger concept to density-dependent predation.Comment: 25 pages, 11 figures, 5 tables, including 2 Supplementary Figures. Version to appear in "Artificial Life

    Can the science of Prosocial be a part of evolution education?

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    We provide a brief overview of Prosocial: Using Evolutionary Science to Build Productive, Equitable, and Collaborative Groups by Paul Atkins, David Sloan Wilson, and Steven Hayes. The book offers a range of promising content for evolution education, and yet also highlights core conceptual challenges in modern evolution science discourse that educators and researchers aiming to improve evolution education may find beneficial to strategically engage with as a scientific community. We discuss these challenges and opportunities with a view towards implications for evolution education research and practice

    Embodied Evolution in Collective Robotics: A Review

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    This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives -- namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a comprehensive summary of research published in the field since its inception (1999-2017), providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an on-line distributed learning method for designing collective behaviours in swarm-like collectives. The paper concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.Comment: 23 pages, 1 figure, 1 tabl

    The resurrection of group selection as a theory of human cooperation

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    Two books edited by members of the MacArthur Norms and Preferences Network (an interdisciplinary group, mainly anthropologists and economists) are reviewed here. These books in large part reflect a renewed interest in group selection that has occurred among these researchers: they promote the theory that human cooperative behavior evolved via selective processes which favored biological and/or cultural group-level adaptations as opposed to individual-level adaptations. In support of this theory, an impressive collection of cross-cultural data are presented which suggest that participants in experimental economic games often do not behave as self-interested income maximizers; this lack of self-interest is regarded as evidence of group selection. In this review, problems with these data and with the theory are discussed. On the data side, it is argued that even if a behavior seems individually-maladaptive in a game context, there is no reason to believe that it would have been that way in ancestral contexts, since the environments of experimental games do not at all resemble those in which ancestral humans would have interacted cooperatively. And on the theory side, it is argued that it is premature to invoke group selection in order to explain human cooperation, because more parsimonious individual-level theories have not yet been exhausted. In summary, these books represent ambitious interdisciplinary contributions on an important topic, and they include unique and useful data; however, they do not make a convincing case that the evolution of human cooperation required group selection
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