A software engineering approach for agent-based modelling and simulation of public goods games

In Agent-based Modelling and Simulation (ABMS), a system is modelled as a collection of agents, which are autonomous decision-making units with diverse characteristics. The interaction of the individual behaviours of the agents results in the global behaviour of the system. Because ABMS offers a methodology to create an artificial society in which actors with their behaviour can be designed and results of their interaction can be observed, it has gained attention in social sciences such as Economics, Ecology, Social Psychology, and Sociology. In Economics, ABMS has been used to model many strategic situations. One of the popular strategic situations is the Public Goods Game (PGG). In the PGG, participants secretly choose how many of their private money units to put into a public pot. Social scientists can conduct laboratory experiments of PGGs to study human behaviours in strategic situations. Research findings from these laboratory studies have inspired studies using computational agents and vice versa. However, there is a lack of guidelines regarding the detailed development process and the modelling of agent behaviour for agent-based models of PGGs. We believe that this has contributed to ABMS of PGG not having been used to its full potential. This thesis aims to leverage the potential of ABMS of PGG, focusing on the development methodology of ABMS and the modelling of agent behaviour. We construct a development framework with incorporated software engineering techniques, then tailored it to ABMS of PGG. The framework uses the Unified Modelling Language (UML) as a standard specification language, and includes a simulation development lifecycle, a step-by-step development guideline, and a short guide for modelling agent behaviour with statecharts. It utilizes software engineering methods to provide a structured approach to identify agent interactions, and design simulation architecture and agent behaviour. The framework is named ABOOMS (Agent-Based Object-Oriented Modelling and Simulation). After applying the ABOOMS framework to three case studies, the framework demonstrates flexibility in development with two different modelling principles (Keep-It-Simple-Stupid vs. Keep-It-Descriptive-Stupid), capability in supporting complex psychological mechanisms, and ability to model dynamic behaviours in both discrete and continuous time. Additionally, the thesis developed an agent-based model of a PGG in a continuous-time setting. To the best of our knowledge such agent-based models do not exist. During the development, a new social preference, Generous Conditional Cooperators, was introduced to better explain the behavioural dynamics in continuous-time PGG. Experimentation with the agent-based model generated dynamics that are not presented in discrete-time setting. Thus, it is important to study both discrete and continuous time PGG, with laboratory experiment and ABMS. Our new framework allows to do the latter in a structured way. With the ABOOMS framework, economists can develop PGG simulation models in a structured way and communicate them with a formal model specification. The thesis also showed that there is a need for further investigation on behaviours in continuous-time PGG. For future works, the framework can be tested with variations of PGG or other related strategic interactions