This project was developed during the Santa Fe course Introduction to Agent-Based Modeling 2022. The origin is a Cellular Automata (CA) model to simulate human interactions that happen in the real world, from Rubens and Oliveira (2009). These authors used a market research with real people in two different times: one at time zero and the second at time zero plus 4 months (longitudinal market research). They developed an agent-based model whose initial condition was inherited from the results of the first market research response values and evolve it to simulate human interactions with Agent-Based Modeling that led to the values of the second market research, without explicitly imposing rules. Then, compared results of the model with the second market research. The model reached 73.80% accuracy.
In the same way, this project is an Exploratory ABM project that models individuals in a closed society whose behavior depends upon the result of interaction with two neighbors within a radius of interaction, one on the relative “right” and other one on the relative “left”. According to the states (colors) of neighbors, a given cellular automata rule is applied, according to the value set in Chooser. Five states were used here and are defined as levels of quality perception, where red (states 0 and 1) means unhappy, state 3 is neutral and green (states 3 and 4) means happy.
There is also a message passing algorithm in the social network, to analyze the flow and spread of information among nodes. Both the cellular automaton and the message passing algorithms were developed using the Python extension. The model also uses extensions csv and arduino.

Local scale mobility, namely foraging, leads to global population dispersal. Agents acquire information about their environment in two ways, one individual and one social. See also http://www.openabm.org/model/3846/

This model allows for oneshot negotiations in the Colored Trails setting. Two allocator agents simultaneously make an offer to a responder agent, who chooses which of these offers to accept, or to reject both offers. The code allows for allocator allocator agents of different orders of theory of mind reasoning to play against one another.

Simulates biobehavioral interactions between 2 populations of hominins.

Biobehavioral interactions between two populations under different movement strategies.

The model simulates the process of widespread diffusion of something due to popularity (i.e., bandwagon) within an organization.

If you have any questions about the model run, please send me an email and I will respond as soon as possible.
Under complex system perspectives, we build the multi-agent system to back-calculate this unification process of the Warring State period, from 32 states in 475 BC to 1 state (Qin) in 221 BC.

Captures interplay between fixed ethnic markers and culturally evolved tags in the evolution of cooperation and ethnocentrism. Agents evolve cultural tags, behavioural game strategies and in-group definitions. Ethnic markers are fixed.

The model examines cattle herd dynamics on a patchy grassland subject to two exogenous pressures: periodic raiding events that remove animals and scheduled management culling that can target males and/or females. It is intended for comparative experiments on how raiding frequency, culling schedules, vegetation dynamics, and life-history parameters interact to shape herd persistence. The model was specifically designed to test the scenario of cattle herding in the arid grasslands of southern Arizona and northern Sonora during the mission period (late 17th through late 18th centuries, CE). In this period, herds were locally managed by Spanish mission personnel and local O’odham groups. Herds were culled mostly for local consumption of meat, hides, and tallow, but the mission herds were often targets for raiding by neighboring groups. The main purpose of the model is to examine herd dynamics in a seasonally variable, arid environment where herds are subject to both intentional internal harvest (culling) and external harvest (raiding).

An ABM to simulate the behaviour of households within a village and observe the emerging properties of the system in terms of food security. The model quantifies food availability, access, utilisation and stability.