Model for the simulation of the Kiss Nightclub fevacuations with agents featring cognition, emotions, emotonal contagion, personality, social relations and norms.

this agent-based model explores the dynamics of volunteer participation in urban community gardens, by combining behavioral theory and institutional theory

This model contains source code and a technical appendix for the paper “Effects of Resource Availability on Consensus Decision Making in Primates”.

Sociodynamica simulates the emergence of cooperation and of economic interactions, showing the synergy achieved by division of labor, the working of shame, and a number of other features that mold the evolution of social cooperation.

This model simulates the household participation in large-scale M. micrantha intervention campaigns and the response of M. micrantha to the intervention.

This model studies the effect of the agents’ adaptive expectation on cooperation frequency in the prisoner’s dilemma game in complex networks from an agent based approach. The model is implemented in Repast simphony 1.2.

This model employs optimal foraging theory principles to generate predictions of which coastal habitats are exploited in climatically stable versus variable environments, using the American Samoa as a study area.

A model for simulating the evolution of individual’s preferences, incliding adaptive agents “falsifying” -as public opinions- their own preferences. It was builded to describe, explore, experiment and understand how simple heuristics can modulate global opinion dynamics. So far two mechanisms are implemented: a version of Festiguer’s reduction of cognitive disonance, and a version of Goffman’s impression management. In certain social contexts -minority, social rank presure- some models agents can “fake” its public opinion while keeping internally the oposite preference, but after a number of rounds following this falsifying behaviour pattern, a coherence principle can change the real or internal preferences close to that expressed in public.

This project attempts to model how social media platforms recommend a user followers based on their interests, and how those individual interests change as a result of the influences from those they follow/are followed by.

We have three types of users on the platform:

Consumers (🔴), who update their interests based on who they’re following.
Creators (⬛), who update their interests based on who’s following them.
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This is a model intended to demonstrate the function of scramble crossings and a more efficient flow of pedestrian traffic with the presence of diagonal crosswalks.