# An Assessment of Agent-Based Modelling Tools for Community-Based Adaptation to Climate Change
## 2 Methodology Adopted  
### Tools Screening and Selection Procedure  
A state-of-the-art database of available ABM tools can be found in [PERSON] et al. [26], a computer science review article titled \"_Agent-Based modelling and Simulation Tools: A Review of State-of-the-Art Software_\", presenting an extensive selection of tools for agent-based modelling encompassing a broad spectrum of domains. [PERSON] et al. [26] describe 82 ABM tools which span a variety of disciplines and the various application cases of ABM tools. However, this article's focus is on tools with the capability to capture and illustrate CBA and its surroundings in a modelling environment, and accordingly, the tools were screened for their CBA relevance by discipline. The criteria to evaluate were chosen based on their relevance to CBA, including their ability to model complex social and environmental interactions, their flexibility in agent definitions, and their support for participatory modelling processes. Each criterion plays a crucial role in ensuring the chosen ABM tool can capture the nuances of CBA. The entire process of selection can be viewed in Figure 1. A database was created with the tools that match the requirements of thematic fields relevant to CBA as follows: social and natural sciences, economics, ecology, urban planning, geographic information system (GIS), and spatial planning. From the initial 82 ABM tools across the various disciplines, a total of 63 ABM tools were identified to match the above-mentioned thematic fields. In the next step, software, technical requirements, and experiment design criteria were screened to further detail needs of tools for the use case of CBA. A database was created for the resulting tools with different properties: licence type, source code, agent type, coding language, model development effort, modelling strength, scalability, and application domain. The study covers the field of CBA, which belongs to the domain of social science. Thus, tools which are compatible with social science, either with social science alone or together with other domains, are considered. In total, 39 tools were identified that meet the mentioned requirements. For this study's purpose, the list was further improved by reducing the number of tools based on the criteria and characteristics listed in Table 2. The relationship between the \"criteria\" and \"characteristics\" columns in Table 2 is established based on practical considerations for selecting ABM tools that can effectively model CBA. Each  
Figure 1: Tool selection process. criterion represents an essential requirement for modelling CBA, while the corresponding characteristic specifies the attribute or capability a tool must possess to meet that criterion. This logical link is grounded in empirical research and practical needs identified in the CBA context. For instance, \"Modelling Strength\" requires tools with \"Medium to High\" capabilities to handle the complexity of climate and extreme event modelling in CBA scenarios, which involve diverse socio-economic and environmental factors. Hence, this alignment ensures that the tools selected are robust enough to capture the nuances of CBA processes and the multifaceted nature of climate adaptation strategies, including the handling of the associated data volumes. Given this study's academic focus, the consideration is directed towards tools that are open source. Recognising the diverse nature of modelling tools and the varying degrees of proficiency they demand, researchers acknowledge that some tools necessitate advanced programming skills, catering to adept programmers or coders. The focus of this article however is on the suitability of the tool to grasp the specificities of the CBA approach, its elements and interactions, as well as surrounding. CBA introduces a layer of complexity given its multifaceted nature. Moreover, CBA deals with intricate environmental dynamics, incorporating data and factors from a wide spectrum, including climate, meteorological data, and various socio-economic elements.