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Abstract: In efforts to resolve social dilemmas, reinforcement learning is an alternative to imitation and exploration in evolutionary game theory. While imitation and exploration rely on the performance of neighbors, in reinforcement learning individuals alter their strategies based on their own performance in the past. For example, according to the Bush-Mosteller model of reinforcement learning, an individual's strategy choice is driven by whether the received payoff satisfies a preset aspiration or not. Stimuli also play a key role in reinforcement learning in that they can determine whether a strategy should be kept or not. Here we use the Monte Carlo method to study pattern formation and phase transitions towards cooperation in social dilemmas that are driven by reinforcement learning. We distinguish local and global players according to the source of the stimulus they experience. While global players receive their stimuli from the whole neighborhood, local players focus solely on individual performance. We show that global players play a decisive role in ensuring cooperation, while local players fail in this regard, although both types of players show properties of "moody cooperators". In particular, global players evoke stronger conditional cooperation in their neighborhoods based on direct reciprocity, which is rooted in the emerging spatial patterns and stronger interfaces around cooperative clusters.
Keywords: evolutionary game theory, cooperation, learning, social physics
Published in DKUM: 03.03.2025; Views: 0; Downloads: 0
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Abstract: Varying environmental conditions affect relations between interacting individuals in social dilemmas, thus affecting also the evolution of cooperation. Oftentimes these environmental variations are seasonal and can therefore be mathematically described as periodic changes. Accordingly, we here study how periodic shifts between different manifestations of social dilemmas affect cooperation. We observe a non-trivial interplay between the inherent spatiotemporal dynamics that characterizes the spreading of cooperation in a particular social dilemma type and the frequency of payoff changes. In particular, we show that periodic changes between two available games with global ordering best be fast, while periodic changes between global and local ordering games best be slow for cooperation to thrive. We also show that the frequency of periodic changes between two local ordering social dilemmas is irrelevant, because then the process is fast and simply the average cooperation level of the two is returned. The structure of the interaction network plays an important role too in that lattices promote local ordering, whilst random graphs hinder the formation of compact cooperative clusters. Conversely, for local ordering the regular structure of the interaction network is only marginally relevant as role-separating checkerboard patterns do not rely on long-range order.
Keywords: cooperation, social dilemma, social physics, phase transition, mixed games
Published in DKUM: 26.02.2025; Views: 0; Downloads: 2
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Abstract: The article examines the prospects for the development of an interstate association of BRICS member nations and concludes that it is necessary to expand cooperation in addition to the economic sphere through other areas, in particular, the organization of interaction to combat crime. The article focuses on the fact that an important area of joint cooperation between the BRICS member nations will be activities in the field of security and combating crime. The main promising areas of cooperation between the BRICS member nations in the field of security are formulated and forms of joint activities in these areas are proposed. This area of cooperation of the BRICS member nations should be based on modern information technologies, which is due to the need for coordination of law enforcement activities of the BRICS member nations. The article analyzes the joint system for preventing international crime in the BRICS member nations and concludes that no improvement of this system is possible without appropriate information support for law enforcement based on general principles and approaches. To this end, the necessity of creating a Unified Digital Environment for Law Enforcement Services in the BRICS member nations is substantiated, which implies the speed of achieving the objectives of law enforcement in the BRICS member nations; reduction of corruption risks in this area; as well as automation of individual work processes by replacing a human resource with software. The article describes the concept of a Unified Digital Environment for Law Enforcement Services of the BRICS member nations, substantiates the components that make up its structure. The modern methods of information processing that can be used to build the specified information system are presented. Possible interested users of this environment are highlighted and the capabilities of the Unified Digital BRICS Law Enforcement Services Environment provided to these users are presented.
Keywords: digital law, digitalization of law, information technology, law enforcement, BRICS, international cooperation, fight against crime, law digital environments
Published in DKUM: 30.01.2025; Views: 0; Downloads: 5
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Abstract: The identification of the most influential individuals in structured populations is an important research question, with many applications across the social and natural sciences. Here, we study this problem in evolutionary populations on static networks, where invading cheaters can lead to the collapse of cooperation. We propose six strategies to rank the invading cheaters and identify those which mostly facilitate the collapse of cooperation. We demonstrate that the type of successful rankings depend on the selection strength, the underlying game, and the network structure. We show that random ranking has generally little ability to successfully identify invading cheaters, especially for the stag-hunt game in scale-free networks and when the selection strength is strong. The ranking based on degree can successfully identify the most influential invaders when the selection strength is weak, while more structured rankings perform better at strong selection. Scale-free networks and strong selection are generally detrimental to the performance of the random ranking, but they are beneficial for the performance of structured rankings. Our research reveals how to identify the most influential invaders using statistical measures in structured communities, and it demonstrates how their success depends on population structure, selection strength, and on the underlying game dynamics.
Keywords: cooperation, cheating, network, population, evolution
Published in DKUM: 07.01.2025; Views: 0; Downloads: 4
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Abstract: Evolutionary games provide the theoretical backbone for many aspects of our social life: from cooperation to crime, from climate inaction to imperfect vaccination and epidemic spreading, from antibiotics overuse to biodiversity preservation. An important, and so far overlooked, aspect of reality is the diverse strategic identities of individuals. While applying the same strategy to all interaction partners may be an acceptable assumption for simpler forms of life, this fails to account for the behavior of more complex living beings. For instance, we humans act differently around different people. Here we show that allowing individuals to adopt different strategies with different partners yields a very rich evolutionary dynamics, including time-dependent coexistence of cooperation and defection, systemwide shifts in the dominant strategy, and maturation in individual choices. Our results are robust to variations in network type and size, and strategy updating rules. Accounting for diverse strategic identities thus has far-reaching implications in the mathematical modeling of social games.
Keywords: cooperation, evolutionary game theory, social physics, collective dynamics, complex system
Published in DKUM: 20.11.2024; Views: 0; Downloads: 4
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