Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.

Studies of colonization processes in past human societies often use a standard population model in which population is represented as a single quantity. Real populations in these processes, however, are structured with internal classes or stages, and classes are sometimes created based on social differentiation. In this present work, information about the colonization of old Providence Island was used to create an agent-based model of the colonization process in a heterogeneous environment for a population with social differentiation. Agents were socially divided into two classes and modeled with dissimilar spatial clustering preferences. The model and simulations assessed the importance of gregarious behavior for colonization processes conducted in heterogeneous environments by socially-differentiated populations. Results suggest that in these conditions, the colonization process starts with an agent cluster in the largest and most suitable area. The spatial distribution of agents maintained a tendency toward randomness as simulation time increased, even when gregariousness values increased. The most conspicuous effects in agent clustering were produced by the initial conditions and behavioral adaptations that increased the agent capacity to access more resources and the likelihood of gregariousness. The approach presented here could be used to analyze past human colonization events or support long-term conceptual design of future human colonization processes with small social formations into unfamiliar and uninhabited environments.

The purpose of this study is another agent-based replication of a System Dynamics model (Anderson,1973) where he analysed the dynamics of nutrient, biomass, oxygen and detritus in a model lake under conditions of artificial fertilising and policies to deal with the consequences of artificial fertilising.. A first replication (Möhring & Troitzsch,2001) added those agents to the original model that were necessary to move the role of the experimenter into the model, whereas this replication replaces the original lake with a collection of small elements between which biomass, nurtrents and oxygen are exchanged, adds rivers upstream and downstream as well as adjacent land divided into villages and populated with farms and industrial plants run by individual persons.

The purpose of this model is to examine equity and efficiency in crop production across a system of irrigated farms, as a function of maintenance costs, assessed water fees, and the capacity of farmers to trade water rights among themselves.

The Communicating Hazard Information in the Modern Environment (CHIME) agent-based model (ABM) is a Netlogo program that facilitates the analysis of information flow and protective decisions across space and time during hazardous weather events. CHIME ABM provides a platform for testing hypotheses about collective human responses to weather forecasts and information flow, using empirical data from historical hurricanes. The model uses real world geographical and hurricane data to set the boundaries of the simulation, and it uses historical hurricane forecast information from the National Hurricane Center to initiate forecast information flow to citizen agents in the model.

ARMM is a theoretical agent-based model that formalizes Murra’s Theory of Verticality (Murra, 1972) to explore how multi-zonal resource management systems emerge in mountain landscapes. The model identifies the social, political, and economic mechanisms that enable vertical complementarity across ecological gradients.
Built in NetLogo, ARMM employs an abstract 111×111 grid divided into four Andean ecological zones (Altiplano, Highland, Lowland, Coast), each containing up to 18 resource types distributed according to ecological suitability. To test general theoretical principles rather than replicate specific geography, resource locations are randomized at each model initialization.
Settlement agents pursue one of two economic strategies: diversification (seeking resource variety, maximum 2 units per type) or accumulation (maximising total quantity, maximum 30 units). Agents move between adjacent zones through hierarchical decision-making, first attempting peaceful interactions—coexistence (governed by tolerance) and trading (governed by cooperation)—before resorting to conflict (theft or takeover, governed by belligerence).
The model demonstrates that vertical complementarity can emerge through fundamentally different mechanisms: either through autonomous mobility under political decentralization or through state-coordinated redistribution under centralization. Sensitivity analysis reveals that belligerence and economic strategy explain approximately 25% of outcome variance, confirming that structural inequalities between zones result from political-economic organization rather than environmental constraints alone.
As a preliminary theoretical model, ARMM intentionally maintains simplicity to isolate core mechanisms and generate testable hypotheses. This foundational framework will guide future empirically-calibrated versions that incorporate specific archaeological settlement data and geographic features from the Carangas region (Bolivia-Chile border), enabling direct comparison between theoretical predictions and observed historical patterns.

This model represents technological and ecological behaviors of mobile hunter-gatherers, in a variable environment, as they produce, use, and discard chipped stone artifacts. The results can be analyzed and compared with archaeological sites.

The model simulates the national Campaign-Based Watershed Management program of Ethiopia. It includes three agents (farmers, Kebele/ village administrator, extension workers) and the physical environment that interact with each other. The physical environment is represented by patches (fields). Farmers make decisions on the locations of micro-watersheds to be developed, participation in campaign works to construct soil and water conservation structures, and maintenance of these structures. These decisions affect the physical environment or generate model outcomes. The model is developed to explore conditions that enhance outcomes of the program by analyzing the effect on the area of land covered and quality of soil and water conservation structures of (1) enhancing farmers awareness and motivation, (2) establishing and strengthening micro-watershed associations, (3) introducing alternative livelihood opportunities, and (4) enhancing the commitment of local government actors.

This model takes concepts from a JASSS paper this is accepted for the October, 2023 edition and applies the concepts to empirical data from counties surrounding and including Cleveland Ohio. The agent-based model has a proportional number of agents in each of the counties to represent the correct proportions of adults in these counties. The adoption decision probability uses the equations from Bass (1969) as adapted by Rand & Rust (2011). It also includes the Outgroup aversion factor from Smaldino, who initially had used a different imitation model on line grid. This model uses preferential attachment network as a metaphor for social networks influencing adoption. The preferential network can be adjusted in the model to be created based on both nodes preferred due to higher rank as well as a mild preference for nodes of a like group.

What is it?

This model demonstrates a very simple bidding market where buyers try to acquire a desired item at the best price in a competitive environment

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