Stabilization of tag-mediated interaction by sexual reproduction in an evolutionary agent system

The evolution of cooperation in a system of agents playing the iterated prisoner's dilemma (IPD) is investigated. We present results for the standard two-person IPD as well as the more general N-person IPD (NIPD) game. In our computational model, agents can recognize each other and decide whether to interact or not, based upon ``tags'' (labels). We consider the evolutionary stability of the evolving populations. Previous work is extended by introducing sexual reproduction (recombination) of agents and by analyzing its influence on the evolving populations. We observed the occasional formation of very stable cooperative societies, as opposed to previous results without sexual reproduction. These cooperative societies are able to resist invasions of ``mimics''(defecting agents with the tag of a cooperating agent)

Effects of Contrarians in the Minority Game

We study the effects of the presence of contrarians in an agent-based model of competing populations. Contrarians are common in societies. These contrarians are agents who deliberately prefer to hold an opinion that is contrary to the prevailing idea of the commons or normal agents. Contrarians are introduced within the context of the Minority Game (MG), which is a binary model for an evolving and adaptive population of agents competing for a limited resource. Results of numerical simulations reveal that the average success rate among the agents depends non-monotonically on the fraction $a_{c}$ of contrarians. For small $a_{c}$, the contrarians systematically outperform the normal agents by avoiding the crowd effect and enhance the overall success rate. For high $a_{c}$, the anti-persistent nature of the MG is disturbed and the few normal agents outperform the contrarians. Qualitative discussion and analytic results for the small $a_{c}$ and high $a_{c}$ regimes are also presented, and the crossover behavior between the two regimes is discussed.Comment: revtex, 11 pages, 4 figure

The Effect of Noise on the Emergence of Continuous Norms and its Evolutionary Dynamics

© 2023 The MIT Press. This is an open access conference proceeding distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/We examine the effect of noise on societies of agents using an agent based model of evolutionary norm emergence. Generally we see that noisy societies are more selfish, smaller and discontent, with noisy societies caught in rounds of perpetual punishment preventing them from flourishing. Surprisingly, despite the detrimental effect of noise on the population, it doesn’t seem to evolve away, in fact, in some cases it seems the level of noise increases. We carry out further analysis and provide reasons for why this might be the case. Furthermore, we claim that our framework evolving the noise/ambiguity of norms is a new way to model the tight/loose framework of norms, suggesting that despite ambiguous norms’ detrimental effect on society, evolution doesn’t favour clarity

Agent-based models and individualism: is the world agent-based?

Agent-based models (ABMs) are an increasingly popular tool in the social sciences. This trend seems likely to continue, so that they will become widely used in geography and in urban and regional planning. We present an overview of examples of these models in the life sciences, economics, planning, sociology, and archaeology. We conclude that ABMs strongly tend towards an individualist view of the social world. This point is reinforced by closer consideration of particular examples. This discussion pays attention to the inadequacy of an individualist model of society with reference to debates in social theory. We argue that because models are closed representations of an open world it is important that institutions and other social structures be explicitly included, or that their omission be explained. A tentative explanation for the bias of ABMs is offered, based on an examination of early research in artificial intelligence and distributed artificial intelligence from which disciplines the approach is derived. Some implications of these findings are discussed. We indicate some useful research directions which are beginning to tackle the individualism issue directly. We further note that the underlying assumptions of ABMs are often hidden in the implementation details. We conclude that such models must be subject to critical examination of their assumptions, and that model builders should engage with social theory if the approach is to realise its full potential