The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) with the addition of group idenetity. We aim at better explaining some patterns generated by this model, using a derived mathematical approximation of the evolution of the opinions averaged.

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. Moreover, each agent belongs to a single group and the opinions within the group are attracted to their average.

We show that a group hierarchy can emerges from this model, and that the inequality of reputations among groups have a negative effect on the opinions about the groups of low status. The mathematical analysis of the opinion dynamic shows that the lower the status of the group, the more detrimental the interactions with the agents of other groups are for the opinions about this group, especially when gossip is activated. However, the interactions between agents of the same group tend to have a positive effect on the opinions about this group.

This model simulates the dynamics of agricultural land use change, specifically the transition between agricultural and non-agricultural land use in a spatial context. It explores the influence of various factors such as agricultural profitability, path dependency, and neighborhood effects on land use decisions.

The model operates on a grid of patches representing land parcels. Each patch can be in one of two states: exploited (green, representing agricultural land) or unexploited (brown, representing non-agricultural land). Agents (patches) transition between these states based on probabilistic rules. The main factors affecting these transitions are agricultural profitability, path dependency, and neighborhood effects.
-Agricultural Profitability: This factor is determined by the prob-agri function, which calculates the probability of a non-agricultural patch converting to agricultural based on income differences between agriculture and other sectors. -Path Dependency: Represented by the path-dependency parameter, it influences the likelihood of patches changing their state based on their current state. It’s a measure of inertia or resistance to change. -Neighborhood Effects: The neighborhood function calculates the number of exploited (agricultural) neighbors of a patch. This influences the decision of a patch to convert to agricultural land, representing the influence of surrounding land use on the decision-making process.

Negotiation plays a fundamental role in shaping human societies, underpinning conflict resolution, institutional design, and economic coordination. This article introduces E³-MAN, a novel multi-agent model for negotiation that integrates individual utility maximization with fairness and institutional legitimacy. Unlike classical approaches grounded solely in game theory, our model incorporates Bayesian opponent modeling, transfer learning from past negotiation domains, and fallback institutional rules to resolve deadlocks. Agents interact in dynamic environments characterized by strategic heterogeneity and asymmetric information, negotiating over multidimensional issues under time constraints. Through extensive simulation experiments, we compare E³-MAN against the Nash bargaining solution and equal-split baselines using key performance metrics: utilitarian efficiency, Nash social welfare, Jain fairness index, Gini coefficient, and institutional compliance. Results show that E³-MAN achieves near-optimal efficiency while significantly improving distributive equity and agreement stability. A legal application simulating multilateral labor arbitration demonstrates that institutional default rules foster more balanced outcomes and increase negotiation success rates from 58% to 98%. By combining computational intelligence with normative constraints, this work contributes to the growing field of socially aware autonomous agents. It offers a virtual laboratory for exploring how simple institutional interventions can enhance justice, cooperation, and robustness in complex socio-legal systems.

This model was designed to study resilience in organizations. Inspired by ethnographic work, it follows the simple goal to understand whether team structure affects the way in which tasks are performed. In so doing, it compares the ‘hybrid’ data-inspired structure with three more traditional structures (i.e. hierarchy, flexible/relaxed hierarchy, and anarchy/disorganization).

The core algorithm is an agent-based model, which simulates travel patterns on a network based on microscopic decision-making by each traveler.

SONG is a simulator designed for simulating the process of transportation network growth.

We built a model using R,polr package, to assess 55 published case studies from developing countries to determine what factors influence the level of compliance of local communities with protected area regulations.

This model investigates the link between prescribed growth in body size, population dynamics and density dependence through population feedback on available resources.

MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.