It is NetLogo reconstruction of the original FORTRAN code of the classical M. Cohen, J. March, and J. Olsen “garbage can model” (GCM or CMO) of collective decision-making.

This version adds a Maslowian entropy to each agent decision based on Kendrick et. al. Rudimentary implementation assumes agents with lower scores are more likely to make decisions autonomously rather than sociotropically.

This is a series of simulations of binary group decisions and the outcomes applied to a generalized version of Price’s Equation for system fitness.

The CHIME ABM explores information distribution networks and agents’ protective decision making in the context of hurricane landfall.

The model aims at estimating household energy consumption and the related greenhouse gas (GHG) emissions reduction based on the behavior of the individual household under different operationalizations of the Theory of Planned Behaviour (TPB).
The original model is developed as a tool to explore households decisions regarding solar panel investments and cumulative consequences of these individual choices (i.e. diffusion of PVs, regional emissions savings, monetary savings). We extend the model to explore a methodological question regarding an interpretation of qualitative concepts from social science theories, specifically Theory of Planned Behaviour in a formal code of quantitative agent-based models (ABMs). We develop 3 versions of the model: one TPB-based ABM designed by the authors and two alternatives inspired by the TPB-ABM of Schwarz and Ernst (2009) and the TPB-ABM of Rai and Robinson (2015). The model is implemented in NetLogo.

This model combines decision making models of individual farmers with a model of the spatial spread between farms of blue tongue virus.

The computer model simulates the development of a social network (i.e. formation of friendships and cliques), the (dyadic) interactions between pupils and the development of similarities and differences in their behavioral profiles.

We built an agent-based model to foster the understanding of homeowners’ insulation activity.

We develop an agent-based model for collective behavior of routine medical check-ups, and specifically dental visits, in a social network.

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.