1. The mix matters : exploring the interplay between epistemic and zetetic norms in scientific disagreementMartin Justin, Dunja Šešelja, Christian Straßer, Borut Trpin, 2025, izvirni znanstveni članek Opis: What is the rational response to a scientific disagreement? Many epistemologists argue that disagreement with an epistemic peer should generally lead to conciliation by lowering confidence in the disputed belief or even suspending judgment altogether. Although this conciliatory approach is widely regarded as a norm of individual rationality, its value in the context of collective scientific inquiry is less clear. Some have even raised concerns that conciliating in scientific disagreements may slow progress or reduce the efficiency of inquiry. In this article,we introduce a novel agent-based model that captures key aspects of scientific disagreement by incorporating both epistemic norms, which govern belief revision, and zetetic norms, which guide how scientists pursue inquiry. Our results indicate that the effects of conciliating in the face of disagreement—whether detrimental or beneficial—depend on the zetetic norms that scientists follow. When scientists focus on exploiting the hypothesis that they believe is most likely to succeed, remaining steadfast is more effective. However, with exploratory scientists, conciliation does not negatively affect group performance. These findings highlight the critical role of zetetic norms in determining the rational response to disagreement in scientific practice.
Ključne besede: scientific disagreement, scientific inquiry, agent-based modeling, Zetetic norms, Bandit models, peer disagreement
Objavljeno v DKUM: 27.08.2025; Ogledov: 0; Prenosov: 6
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2. Dissimilarity-driven behavior and cooperation in the spatial public goods gameYinhai Fang, Tina Perc Benko, Matjaž Perc, Haiyan Xu, 2019, izvirni znanstveni članek Opis: In this paper, we explore the impact of four different types of dissimilarity-driven behavior on the evolution of cooperation in the spatial public goods game. While it is commonly assumed that individuals adapt their strategy by imitating one of their more successful neighbors, in reality only very few will be awarded the highest payoffs. Many have equity or equality preferences, and they have to make do with an average or even with a low payoff. To account for this, we divide the population into two categories. One consists of payoff-driven players, while the other consists of dissimilarity-driven players. The later imitate the minority strategy in their group based on four different dissimilaritydriven behaviors. The rule that most effectively promotes cooperation, and this regardless of the multiplication factor of the public goods game, is when individuals adopt the minority strategy only when their payoff is better than that of their neighbors. If the dissimilarity-driven players adopt the minority strategy regardless of the payoffs of others, or if their payoff is the same, the population typically evolves towards a neutral state where cooperators and defectors are equally common. This may be beneficial when the multiplication factor is low, when defectors would otherwise dominate. However, if the dissimilarity-driven players adopt the minority strategy only when their payoff is worse than that of their neighbors, then cooperation is not promoted at all in comparison to the baseline case in the absence of dissimilarity-driven behavior. We explore the pattern formation behind these results, and we discuss their wider implications for the better understanding of cooperative behavior in social groups.
Ključne besede: theoretical biology, evolution, agent-based modeling, complex system, network science, evolutionary game theory
Objavljeno v DKUM: 26.02.2025; Ogledov: 0; Prenosov: 8
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3. Identification of influential invaders in evolutionary populationsGuoli Yang, Tina Perc Benko, Matteo Cavaliere, Jincai Huang, Matjaž Perc, 2019, izvirni znanstveni članek Opis: The identification of the most influential nodes has been a vibrant subject of research across the whole of network science. Here we map this problem to structured evolutionary populations, where strategies and the interaction network are both subject to change over time based on social inheritance. We study cooperative communities, which cheaters can invade because they avoid the cost of contributions that are associated with cooperation. The question that we seek to answer is at which nodes cheaters invade most successfully. We propose the weighted degree decomposition to identify and rank the most influential invaders. More specifically, we distinguish two kinds of ranking based on the weighted degree decomposition. We show that a ranking strategy based on negative-weighted degree allows to successfully identify the most influential invaders in the case of weak selection, while a ranking strategy based on positive-weighted degree performs better when the selection is strong. Our research thus reveals how to identify the most influential invaders based on statistical measures in dynamically evolving cooperative communities.
Ključne besede: theoretical biology, evolution, agent-based modeling, complex system, network science, evolutionary game theory
Objavljeno v DKUM: 26.02.2025; Ogledov: 0; Prenosov: 4
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