Agent Based Modeling

Coping with increasing tides: Evolving agglomeration dynamics and technological change under exacerbating hazards

Cities are the engine of the world economy: they provide jobs, cultural and educational amenities, and serve as incubators of innovations. By 2050 up to 70% of the world's population is expected to live in cities, many of which, for a variety of historical reasons - such as access to natural amenities, resources, or strategic...

Agent-based modelling of post-disaster recovery with remote sensing data

In this recent study, we develop an agent-based model using machine learning-derived information from remote sensing data to simulate and explore the post-disaster recovery processes in urban areas of Tacloban, the Philippines, devastated by Typhoon Haiyan in 2013.

Download BENCH agent based model

Open Access agent-based model to study shifts in residential energy use and corresponding emissions driven by behavioral changes among heterogeneous individuals.

Download ABM of households PV investments

Open Access agent-based model to explore diffusion of households' solar panel investment decisions and their regional impacts in terms of CO2 reductions and monetary gains of heterogeneous households.

Download ABM of post-disaster recovery

Open Access agent-based model to model urban recovery processes driven by location choices of diverse households.

A review of agent-based flood risk models

In this paper, we systematically reviewed the ABMs that explore mid to long-term reactions of socio-economic systems to flood hazards...

Download our ABM model on risk perception and housing prices

Open Access agent-based model to simulate the aggregated impacts of households’ residential location choices and their changing risk perceptions in response to flooding.

Socio-economic data from slums in Bangalore, India

Our results suggest that pure market-driven processes can cause shifts in demographics in climate-sensitive hotspots placing low-income households further at risk...

Repetitive floods intensify outmigration and climate gentrification in coastal cities

Our results suggest that pure market-driven processes can cause shifts in demographics in climate-sensitive hotspots placing low-income households further at risk...

Empirical agent-based land market in urban land-use models

This paper introduces an economic agent-based model of an urban housing market. Our Risks and Hedonics in Empirical Agent-based land market (RHEA) model captures natural hazard risks and environmental amenities through hedonic analysis, facilitating empirical agent-based land market modeling.
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Agent Based Modeling

Agent-based model is a computer code representing how many heterogeneous adaptive economic agents – households, firms, farmers, governmental institutions – make decisions and interact with each other and their environment according to different behavioral rules.