Substitution of food products will be key to realising widespread adoption of sustainable diets. We present an agent-based model of decision-making and influences on food choice, and apply it to historically observed trends of British whole and skimmed (including semi) milk consumption from 1974 to 2005. We aim to give a plausible representation of milk choice substitution, and test different mechanisms of choice consideration. Agents are consumers that perceive information regarding the two milk choices, and hold values that inform their position on the health and environmental impact of those choices. Habit, social influence and post-decision evaluation are modelled. Representative survey data on human values and long-running public concerns empirically inform the model. An experiment was run to compare two model variants by how they perform in reproducing these trends. This was measured by recording mean weekly milk consumption per person. The variants differed in how agents became disposed to consider alternative milk choices. One followed a threshold approach, the other was probability based. All other model aspects remained unchanged. An optimisation exercise via an evolutionary algorithm was used to calibrate the model variants independently to observed data. Following calibration, uncertainty and global variance-based temporal sensitivity analysis were conducted. Both model variants were able to reproduce the general pattern of historical milk consumption, however, the probability-based approach gave a closer fit to the observed data, but over a wider range of uncertainty. This responds to, and further highlights, the need for research that looks at, and compares, different models of human decision-making in agent-based and simulation models. This study is the first to present an agent-based modelling of food choice substitution in the context of British milk consumption. It can serve as a valuable pre-curser to the modelling of dietary shift and sustainable product substitution to plant-based alternatives in Britain.

Pastoralscape is a model of human agents, lifestock health and contageous disease for studying the impact of human decision making in pastoral communities within East Africa on livestock populations. It implements an event-driven agent based model in Python 3.

Signaling chains are a special case of Lewis’ signaling games on networks. In a signaling chain, a sender tries to send a single unit of information to a receiver through a chain of players that do not share a common signaling system.

This model couples a two-asset heterogeneous-agent New Keynesian macroeconomy with a household layer that can be driven in two ways. One is a conventional calibration. The other is a set of large-language-model persona agents built from real survey households in Korea (NaSTaB), the United States (PSID) and Italy (SHIW). Each persona is given its balance sheet, income and prices, and reports consumption, saving and labour supply. A feasibility layer enforces the budget constraint. A conditional-mean surrogate then turns these decisions into a propensity surface. That surface reaches the macroeconomic block through a single channel, the intertemporal marginal propensity to consume matrix. Because of this, a calibrated “twin” can be aligned with the generative layer exactly, and the two can be compared policy by policy.

Both layers are then scored against the held-out consumption of the same households. The model’s role is to serve as a benchmark: it tests whether generative agents add information beyond the balance sheet, and whether that information matches real behaviour.

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This model extends Schelling’s segregation model with mobility sharing. Agents of two groups occupy cells of a 32 × 32 grid and repeatedly choose activity destinations subject to a preference threshold, the minimum share of ingroup neighbours they accept. Trips are matched into shared rides between members of different groups, using one of four matching algorithms on a shareability network (maximal cross-group matching, maximum weight matching on contact time, maximum cardinality matching, or random greedy matching) with a maximum detour constraint. After each trip, an agent’s preference threshold changes with the time spent in contact with outgroup members.

Starting from complete segregation, the model examines under which conditions contact during shared trips leads to integration. Besides the main scenario, in which contact always lowers the threshold, it includes two extensions. In the first, a share of adversarial agents becomes less tolerant with contact, and this share grows or shrinks with the current level of segregation, governed by a branching dissimilarity index and a conversion rate. In the second, each contact raises or lowers the threshold with a probability that depends on the agent’s current attitude relative to a compatibility threshold.

Segregation is measured with the index of dissimilarity and the Gini coefficient. The model file includes BehaviorSpace experiments for each analysis in the associated article. The matching step uses the NetworkX library through the Python extension of NetLogo (requires Python 3 with numpy and networkx 3.x).

The agent based model matches origins and destinations using employment search methods at the individual level.

An agent-based model is used to simulate legislators’ behavior under secret voting rules, as influenced by the power of the accused politician, the composition of the voting body, and the publicity of the accusations.

Simulation to replicate and extend an analytical model (Konrad & Skaperdas, 2010) of the provision of security as a collective good. We simulate bandits preying upon peasants in an anarchy condition.

This model is to match students and schools using real-world student admission mechanisms. The mechanisms in this model are serial dictatorship, deferred acceptance, the Boston mechanism, Chinese Parallel, and the Taipei mechanism.

LUXE is a land-use change model featuring different levels of land market implementation. It integrates utility measures, budget constraints, competitive bidding, and market interactions to model land-use change in exurban environment.