The network-based trust game is a hybridization of both the repeated trust games and the network games.

What is it?

This model demonstrates a very simple bidding market where buyers try to acquire a desired item at the best price in a competitive environment

…

CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

This model was build to explore the bio-cultural interaction between AMH and Neanderthals during the Middle to Upper Paleolithic Transition in the Iberian Peninsula

This is model that explores how a few farmers in a Chinese village, where all farmers are smallholders originally, reach optimal farming scale by transferring in farmland from other farmers in the context of urbanization and aging.

Netlogo model that shows how the cooling process determines the quality of a solution in simulated annealing using Metropolis algorithm.

This is a stylized model based on Alonso’s model investigating the relationship between urban sprawl and income segregation.

The ForagerNet3_Demography model is a non-spatial ABM designed to serve as a platform for exploring several aspects of hunter-gatherer demography.

MOSAIC is an agent-based NetLogo model of decentralized mission coordination among heterogeneous robots operating under partial observability, limited energy, spatially variable risk, dynamic communication, and individual and cooperative task requirements. Robots discover tasks locally, exchange task information through temporary communication links, submit capability-, energy-, deadline-, and risk-aware bids, compete for individual contracts, and form temporary coalitions for cooperative tasks.

The model integrates decentralized auctions, greedy capability-based coalition formation, contract release and reassignment, four reward regimes, reputation, adaptive bidding strategies, failure traceability, and mission-, network-, information-, inequality-, and coalition-level metrics. It operates without a centralized mission planner or global combinatorial assignment solver.

Seven paired-seed BehaviorSpace experiments comprising 690 official simulation runs evaluate baseline mission viability, reward regimes, communication structure, capability heterogeneity, cooperative-task demand, reputation and adaptive strategies, and mission-incentive strength. The results indicate that structural coordination capacity—particularly information reach, capability compatibility, and feasible coalition construction—has a stronger effect on mission completion than increasing incentive intensity within the tested architecture and parameter ranges.

…

The model’s aim is to represent the price dynamics under very simple market conditions, given the values adopted by the user for the model parameters. We suppose the market of a financial asset contains agents on the hypothesis they have zero-intelligence. In each period, a certain amount of agents are randomly selected to participate to the market. Each of these agents decides, in a equiprobable way, between proposing to make a transaction (talk = 1) or not (talk = 0). Again in an equiprobable way, each participating agent decides to speak on the supply (ask) or the demand side (bid) of the market, and proposes a volume of assets, where this number is drawn randomly from a uniform distribution. The granularity depends on various factors, including market conventions, the type of assets or goods being traded, and regulatory requirements. In some markets, high granularity is essential to capture small price movements accurately, while in others, coarser granularity is sufficient due to the nature of the assets or goods being traded