This is a gender differentiation model in terms of reputations, prestige and self-esteem (presented in the paper https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236840). The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) considering two groups.

This agent-based model studies how inequalities can be explained by the difference of open-mindness between two groups of interacting agents. We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters. We study an heterogeneous population of two different groups: one more open to influence of others, taking less into account their perceived difference of esteem, called L; a second one less prone to it, called S, who designed the credibility they give to others strongly based on how higher or lower valued than themselves they perceive them.

We show that a mixed population always turns in favor to some agents belonging to the group of less open-minded agents S, and harms the other group: (1) the average group self-opinion or reputation of S is always better than the one of L; (2) the higher rank in terms of reputation are more frequently occupied by the S agents while the L agents occupy more the bottom rank; (3) the properties of the dynamics of differentiation between the two groups are similar to the properties of the glass ceiling effect proposed by Cotter et al (2001).

We introduce a model of prediction markets that uses opinion dynamics as its underlying mechanism for price formation. We base the opinion dynamics on the Deffuant model of bounded rationality. We have used this model to show that price formation in prediction markets can be robustly explained by opinion dynamics, and that the model can also explain phase transitions depending on just two parameters.

The model provides instruments for the simulation of interbank network evolution. There are tools for dynamic network analysis, allowing to evaluate graph topological invariants, thermodynamic network features and combinational node-based features.

This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.

Designed to capture the evolutionary forces of global society.

This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.

The model’s purpose is to provide a potential explanation for the emergence, sustenance and decline of unpopular norms based on pluralistic ignorance on a social network.

We model the epistemic dynamics preceding political uprising. Before deciding whether to start protests, agents need to estimate the amount of discontent with the regime. This model simulates the dynamics of group knowledge about general discontent.

Transhumants move their herds based on strategies simultaneously considering several environmental and socio-economic factors. There is no agreement on the influence of each factor in these strategies. In addition, there is a discussion about the social aspect of transhumance and how to manage pastoral space. In this context, agent-based modeling can analyze herd movements according to the strategy based on factors favored by the transhumant. This article presents a reductionist agent-based model that simulates herd movements based on a single factor. Model simulations based on algorithms to formalize the behavioral dynamics of transhumants through their strategies. The model results establish that vegetation, water outlets and the socio-economic network of transhumants have a significant temporal impact on transhumance. Water outlets and the socio-economic network have a significant spatial impact. The significant impact of the socio-economic factor demonstrates the social dimension of Sahelian transhumance. Veterinarians and markets have an insignificant spatio-temporal impact. To manage pastoral space, water outlets should be at least 15 km
from each other. The construction of veterinary centers, markets and the securitization of transhumance should be carried out close to villages and rangelands.

AncientS-ABM is an agent-based model for simulating and evaluating the potential social organization of an artificial past society, configured by available archaeological data. Unlike most existing agent-based models used in archaeology, our ABM framework includes completely autonomous, utility-based agents. It also incorporates different social organization paradigms, different decision-making processes, and also different cultivation technologies used in ancient societies. Equipped with such paradigms, the model allows us to explore the transition from a simple to a more complex society by focusing on the historical social dynamics; and to assess the influence of social organization on agents’ population growth, agent community numbers, sizes and distribution.

AncientS-ABM also blends ideas from evolutionary game theory with multi-agent systems’ self-organization. We model the evolution of social behaviours in a population of strategically interacting agents in repeated games where they exchange resources (utility) with others. The results of the games contribute to both the continuous re-organization of the social structure, and the progressive adoption of the most successful agent strategies. Agent population is not fixed, but fluctuates over time, while agents in stage games also receive non-static payoffs, in contrast to most games studied in the literature. To tackle this, we defined a novel formulation of the evolutionary dynamics via assessing agents’ rather than strategies’ fitness.

As a case study, we employ AncientS-ABM to evaluate the impact of the implemented social organization paradigms on an artificial Bronze Age “Minoan” society, located at different geographical parts of the island of Crete, Greece. Model parameter choices are based on archaeological evidence and studies, but are not biased towards any specific assumption. Results over a number of different simulation scenarios demonstrate better sustainability for settlements consisting of and adopting a socio-economic organization model based on self-organization, where a “heterarchical” social structure emerges. Results also demonstrate that successful agent societies adopt an evolutionary approach where cooperation is an emergent strategic behaviour. In simulation scenarios where the natural disaster module was enabled, we observe noticeable changes in the settlements’ distribution, relating to significantly higher migration rates immediately after the modeled Theran eruption. In addition, the initially cooperative behaviour is transformed to a non-cooperative one, thus providing support for archaeological theories suggesting that the volcanic eruption led to a clear breakdown of the Minoan socio-economic system.

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