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Emergence of Innovation and Cooperation
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Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life316-323, (July 29–August 2, 2019) 10.1162/isal_a_00181
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The design of mechanisms that encourage pro-social behaviours in populations of self-regarding agents is recognised as a major theoretical challenge within several areas of social, life and engineering sciences. When interference from external parties is considered, several heuristics have been identified as capable of engineering a desired collective behaviour at a minimal cost. However, these studies neglect the diverse nature of contexts and social structures that characterise real-world populations. Here we analyse the impact of diversity by means of scale-free interaction networks with high and low levels of clustering, and test various interference mechanisms using simulations of agents facing a cooperative dilemma. Our results show that interference on scale-free networks is not trivial and that distinct levels of clustering react differently to each interference mechanism. As such, we argue that no tailored response fits all scale-free networks and present which mechanisms are more efficient at fostering cooperation in both types of networks. Finally, we discuss the pitfalls of considering reckless interference mechanisms.
Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life308-315, (July 29–August 2, 2019) 10.1162/isal_a_00180
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We simulate an ant colony in which an ant’s genetics can determine behavioral, morphological and physiological differences between workers and queens. We show that depending on the benefits conferred to workers and queens different reproductive division of labor strategies evolve. In particular, we observe both generalist colonies and colonies with specialized worker and queen castes. Generalist colonies were subject to selection for optimal response thresholds. Colonies with castes evolved a discrete queen caste and either a discrete or continuous worker caste. As a secondary experiment we expose our evolved colonies to a changing environment to test their ability to adapt cooperative foraging strategies and we find all reproductive division of labor strategies were effective at cooperative foraging.
Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life333-340, (July 29–August 2, 2019) 10.1162/isal_a_00184
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Collaboration in order to perform various tasks such as herding or hunting is frequently seen in nature. Cooperative behaviors benefit the group by helping them achieve rewards that would not be possible for an individual to achieve alone. In addition to cooperative hunting, spotted hyenas also participate in coordinated mobbing of lions, which is a complex behavior that is still believed to be genetic. Lions are larger and stronger than hyenas, and therefore the hyenas need to cooperate in large numbers to overcome their fear and attack the lions. Individualistic hyena traits and other factors that may affect the frequency or success of lion-mobbing have not been studied in simulation before. Furthermore, multiple emotions, such as fear and affiliation towards teammates, affect the willingness of hyenas to attack lions. The computational model of lion-hyena interaction developed in this work can help understand the evolution of mobbing behaviors. It may be used in the future to evolve strategies in video game characters to overcome powerful adversaries or solve problems that involve high risk.
Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life300-307, (July 29–August 2, 2019) 10.1162/isal_a_00179
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Fitness improving innovations occur in populations of organisms as genetic changes (mutations) that allow better fit with the environmental niche of the organisms. Similarly, fitness improving innovations may occur in the context of human communities as well in terms of socio-economic innovations (e.g. new ways of organizing the military, new products or services) that lead to more efficient use of available resources. Here we explore the link between such innovations and the harshness of the environment, where the populations live. Environmental harshness characterizes the availability of population growth supporting resources in the environment. Our analysis shows that if the harshness of the environment varies smoothly with the distance, the expected extent of fitness improving innovations and of the resource utilization efficiency of populations depends in a combined linear and harmonic manner on the harshness of the environment at the location of origin of the populations. We explore the implications of this result for particular cases of both biological and social environments (e.g. gene drives, business innovation).
Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life331-332, (July 29–August 2, 2019) 10.1162/isal_a_00183
Proceedings Papers
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life324-330, (July 29–August 2, 2019) 10.1162/isal_a_00182
Abstract
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We present a model for the spread, transmission and competition of skills with an emphasis on the role of spatial mobility of individuals. From a methodological point of view, we seek mathematical and computational simplicity in the sense of a minimal model. This minimalism lets us use a infinite dimensional simplex space and not a Euclidean space as underlying structure. Such a simplex captures the essentials of spatial heterogeneity without the mathematical difficulties of neighborhood structures. In the presented model, individuals may have no skill or either skill A or B. Individuals are born unskilled and may acquire skills by learning from a skilled individual. Skill A results in a small reproductive advantage and is easy to transmit (teaching happens at high rate), whereas skill B is harder to teach but results in a high benefit. The model exhibits a rich behavior; after an initial transient, the system settles to a fix point (constant distribution of skills), whereby the distribution of skills depends on a mobility parameter m. We observe different regimes, and as the main result, we conclude that for some settings of the system parameters, the spread of the (harder to learn but more beneficial) skill B is only possible within a specific range of the mobility parameter. From a technical point of view, this paper presents the application of the PRESS–method (probability reduced evolution of spatially resolved species) that enables the study of spatial effects in a very efficient manner. We analyze the consequences of spatial organization and argue that we can study aspects of social dynamics in an infinite dimensional simplex space. In spite of this maybe daunting name, the dynamics on such a structure is comparably easy to implement. The model we present is far from reflecting all the details of human interaction. On the contrary, we deliberately tailored the model to be as simple as possible from a mathematical point of view (but still reflecting central properties of spatial organization). This approach is guided by physics, where seemingly simple models which obviously don’t reflect the true physical behavior of a system (such as the Ising model) are nevertheless suited to reveal fundamental aspects and limiting cases of the real world.