The Simulating Agroforestry Adoption in Rural Indonesia (SAFARI) model aims at exploring the adoption of illipe rubber agroforestry systems by farming households in the case study region in rural Indonesia. Thereby, the ABM simulates the interdependencies of agroforestry systems and local livelihoods, income, land use, biodiversity, and carbon fixation. The model contrasts development paths without agroforestry (business as usual (BAU) scenario), corresponding to a scenario where the government promotes rubber monoculture, with the introduction of illipe rubber agroforestry systems (IRA scenario) as an alternative. It aims to support policy-makers to assess the potential of IRA over larger temporal and spatial scales.

This model implements a bidirectional coupling between micro-level agent decisions and macro-level system dynamics, with an additional diagnostic layer based on Stafford Beer’s Viable System Model.

Key features:
- Six types of agents (Household, Firm, Bank, Government, Foreign, Innovation)
- Continuous SDM core integrated with Runge-Kutta 4
- Robust GDELT data handling with multi-level fallback
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The model demonstrates how non-instantaneous sampling techniques produce bias by overestimating the number of counted animals, when they move relative to the person counting them.

The purpose of this hybrid ABM is to answer the question: where is the best place for a new swimming pool in a region of Krakow (in Poland)?

The model is well described in ODD protocol, that can be found in the end of my article published in JASSS journal (available online: http://jasss.soc.surrey.ac.uk/22/1/1.html ). Comparison of this kind of models with spatial interaction ones, is presented in the article. Before developing the model for different purposes, area of interest or services, I recommend reading ODD protocol and the article.

I published two films on YouTube that present the model: https://www.youtube.com/watch?v=iFWG2Xv20Ss , https://www.youtube.com/watch?v=tDTtcscyTdI&t=1s

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Amidst the global trend of increasing market concentration, this paper examines the role of finance
in shaping it. Using Agent-Based Modeling (ABM), we analyze the impact of financial policies on market concentration
and its closely related variables: economic growth and labor income share. We extend the Keynes
meets Schumpeter (K+S) model by incorporating two critical assumptions that influence market concentration.
Policy experiments are conducted with a model validated against historical trends in South Korea. For policy
variables, the Debt-to-Sales Ratio (DSR) limit and interest rate are used as levers to regulate the quantity and
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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.

Swidden Farming is designed to explore the dynamics of agricultural land management strategies.

An algorithm implemented in NetLogo that can be used for searching resources.

This model simulates household water consumption patterns in an urban environment. Its current setup compares monthly water consumption data, and the results of a daily heuristic water demand model with the simulation results produced by household demographics that is fine tuned via some base demand model. It’s designed to estimate and analyze water demand based on various factors including household demographics, daily routines of residents (working, weekending, vacation patterns), weather conditions (temperature and precipitation), appliance usage patterns, seasonal variations, and special periods such as weekends and holidays. The model aims to help understand how different factors influence residential water consumption and can be used for water demand forecasting and management.

This is an Agent Based Model of a generic food chain network consisting of stylized individuals representing producers, traders, and consumers. It is developed to: 1/ to describe the dynamically changing disaggregated flows of crop items between these agents, and 2/ to be able to explicitly consider agent behavior. The agents have implicit personal objectives for trading. Resilience and efficiency are quantified using the ascendency concept by linking these to the fraction of fulfillment of the overall explicit objective to have all consumers meet their food requirement. Different types of network structures in combination with different agent interaction types under different types of stylized shocks can be simulated.