Evolution of swarming behavior is shaped by how predators attack

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

Mapping posthuman discourse and the evolution of living information

The discourse that surrounds and constitutes the post-human emerged as a response to earlier claims of an essential or universal human or human nature. These discussions claim that the human is a discursive construct that emerges from various configurations of nature, embodiment, technology, and culture, configurations that have also been variously shaped by the forces of social history. And in the absence of an essential human figure, post-human discourses suggest that there are no restrictions or limitations on how the human can be reconfigured. This axiom has been extended in light of a plethora of technological reconfigurations and augmentations now potentially available to the human, and claims emerge from within this literature that these new technologies constitute a range of possibilities for future human biological evolution. This thesis questions the assumption contained within these discourses that technological incursions or reconfigurations of the biological human necessarily constitute human biological or human social evolution by discussing the role the evolution theories plays in our understanding of the human, the social, and technology. In this thesis I show that, in a reciprocal process, evolution theory draws metaphors from social institutions and ideologies, while social institutions and ideologies simultaneously draw on metaphors from evolution theory. Through this discussion, I propose a form of evolution literacy; a tool, I argue, is warranted in developing a sophisticated response to changes in both human shape and form. I argue that, as a whole, our understanding of evolution constitutes a metanarrative, a metaphor through which we understand the place of the human within the world; it follows that historical shifts in social paradigms will result in new definitions of evolution. I show that contemporary evolution theory reflects parts of the world as codified informatic systems of associated computational network logic through which the behaviour of participants is predefined according to an evolved or programmed structure. Working from within the discourse of contemporary evolution theory I develop a space through which a version of the post-human figure emerges. I promote this version of the post-human as an Artificial Intelligence computational programme or autonomous agent that, rather than seeking to replace, reduce or deny the human subject, is configured as an exosomatic supplement to and an extension of the biological human

The evolutionary origins of hierarchy

Hierarchical organization -- the recursive composition of sub-modules -- is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force--the cost of connections--promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.Comment: 32 page

Building a Science of Animal Minds: Lloyd Morgan, Experimentation, and Morgan’s Canon

Conwy Lloyd Morgan (1852–1936) is widely regarded as the father of modern comparative psychology. Yet, Morgan initially had significant doubts about whether a genuine science of comparative psychology was even possible, only later becoming more optimistic about our ability to make reliable inferences about the mental capacities of non-human animals. There has been a fair amount of disagreement amongst scholars of Morgan’s work about the nature, timing, and causes of this shift in Morgan’s thinking. We argue that Morgan underwent two quite different shifts of attitude towards the proper practice of comparative psychology. The first was a qualified acceptance of the Romanesian approach to comparative psychology that he had initially criticized. The second was a shift away from Romanes’ reliance on systematizing anecdotal evidence of animal intelligence towards an experimental approach, focused on studying the development of behaviour. We emphasize the role of Morgan’s evolving epistemological views in bringing about the first shift – in particular, his philosophy of science. We emphasize the role of an intriguing but overlooked figure in the history of comparative psychology in explaining the second shift, T. Mann Jones, whose correspondence with Morgan provided an important catalyst for Morgan’s experimental turn, particularly the special focus on development. We also shed light on the intended function of Morgan’s Canon, the methodological principle for which Morgan is now mostly known. The Canon can only be properly understood by seeing it in the context of Morgan’s own unique experimental vision for comparative psychology

The dynamics of Machiavellian intelligence

The "Machiavellian intelligence" hypothesis (or the "social brain" hypothesis) posits that large brains and distinctive cognitive abilities of humans have evolved via intense social competition in which social competitors developed increasingly sophisticated "Machiavellian" strategies as a means to achieve higher social and reproductive success. Here we build a mathematical model aiming to explore this hypothesis. In the model, genes control brains which invent and learn strategies (memes) which are used by males to gain advantage in competition for mates. We show that the dynamics of intelligence has three distinct phases. During the dormant phase only newly invented memes are present in the population. During the cognitive explosion phase the population's meme count and the learning ability, cerebral capacity (controlling the number of different memes that the brain can learn and use), and Machiavellian fitness of individuals increase in a runaway fashion. During the saturation phase natural selection resulting from the costs of having large brains checks further increases in cognitive abilities. Overall, our results suggest that the mechanisms underlying the "Machiavellian intelligence" hypothesis can indeed result in the evolution of significant cognitive abilities on the time scale of 10 to 20 thousand generations. We show that cerebral capacity evolves faster and to a larger degree than learning ability. Our model suggests that there may be a tendency toward a reduction in cognitive abilities (driven by the costs of having a large brain) as the reproductive advantage of having a large brain decreases and the exposure to memes increases in modern societies.Comment: A revised version has been published by PNA

Some philosophical enquiries on E-learning: preparing the tomorrow business school

Emerging digital technologies and increasing interest in the computerized delivery of higher education have led to e-learning through electronic mail, the Internet, the World Wide Web (WWW), and multimedia. The major objective of this research outlet is to examine the e-learning evolution in business schools. Our research intentions are to investigate: 1. if universities understand the market dynamics (regarding to segmentation and crossing the chasm); 2. mapping the s-curve to student needs and 3. how business schools will change the value map. From the analysis of existing empirical evidence and our research results from 140 business students of the University of Ioannina (Greece) and 50 business students of the University of Winchester (UK), we can summarize that: a. value is created when new technology is matched to student need; b. but student needs change: as the technology evolves existing students develop new needs and in addition the technology may appeal to new kinds of students, with new kinds of needs and c. understanding the structure of student needs may be particularly important at times of potential discontinuity, when existing students may reject new technologies (for excellent reasons!).  The authors suggest that business schools interested in being productive should invest in implementing performance tools for all educational methods in order to accomplish the educational objectives. Further research in this crucial field of the evolution of e-learning in business schools is the examination of anticipated benefits and the experiences by early e-learning adopters, return on investment and expectations for the future