Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of assessing their effects on a system as a whole. Several frameworks for generating parallel ABMS applications have been developed taking advantage of their common characteristics, but there is a lack of a general benchmark for comparing the performance of generated applications. We propose and design a benchmark that takes into consideration the most common characteristics of this type of applications and includes parameters for influencing their relevant performance aspects. We provide an initial implementation of the benchmark for FLAME one of the most popular parallel ABMS platforms, and we use it for comparing the applications generated by these platforms.

This model is a market game for evaluating the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering in the UK retail electricity market. We break down the policy into four

The ABM looks at how the performance of Water Service Delivery is affected by the relation between management practices and integrity in terms of transparency, accountability and participation

The purpose of this model is to enhance a basic ABM through a simple set of rules identified using the activity-driven models in order to produce more realistic patterns of pedestrian movement.

This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

The Li-BIM model aims at simulating the behavior of occupants in a building. It is structured around the numerical modeling of the building (IFC format) and a BDI cognitive architecture. The model has been implemented under the GAMA platform.

This agent-based model explores the existence of positive feedback loops related to illegal, unregulated, unreported (IUU) fishing; the use of forced labor; and the depletion of fish populations due to commercial fishing.

The Mission San Diego model is an epidemiological model designed to test hypotheses related to the spread of the 1805-1806 measles epidemic among indigenous residents of Mission San Diego during the early mission period in Alta California. The model community is based on the population of the Mission San Diego community, as listed in the parish documents (baptismal, marriage, and death records). Model agents are placed on a map-like grid that consists of houses, the mission church, a women’s dormitory (monjeria) adjacent to the church, a communal kitchen, priest’s quarters, and agricultural fields. They engage in daily activities that reflect known ethnographic patterns of behavior at the mission. A pathogen is introduced into the community and then it spreads throughout the population as a consequence of individual agent movements and interactions.

This model is part of an article that discusses the adoption of a complexity theory approach to study the dynamics of language contact within multilingual communities. The model simulates the dynamics of communication within a community where a minority and a majority group coexist. The individual choice of language for communication is based on a number of simple rules derived from a review of the main literature on the topic of language contact. These rules are then combined with different variables, such as the rate of exogamy of the minority group and the presence of relevant education policies, to estimate the trends of assimilation of the minority group into the majority one. The model is validated using actually observed data from the case of Romansh speakers in the canton of Grisons, Switzerland.

This model inspects the performance of firms as the product attribute space changes, which evolves as a consequence of firms’ actions. Firms may create new product variants by dragging demand from other existing variants. Firms decide whether to open new product variants, to invade existing ones, or to keep their variant portfolio. At each variant there is a Cournot competition each round. Competition is nested since many firms compete at many variants simultaneously, affecting firm composition at each location (variant).

After the Cournot outcomes, at each round firms decide whether to (i) keep their existing product variant niche, (ii) invade an existing variant, (iii) create a new variant, or (iv) abandon a variant. Firms’ profits across their niche take into consideration the niche-width cost and the cost of opening a new variant.