Agent-based modelling and simulation (ABMS) is highly instrumental for studying socio-technical systems. MAIA – Modelling Agents using Institutional Analysis – is an ABMS modelling framework that formalises social sciences knowledge. It enables handling the complexity of large complex systems, allows collaborative model development and the reuse of model components when building simulations. We detail the procedural semantics for transforming a MAIA model into an executable simulation. Its evaluation through various case studies of model development and simulation is described. The MAIA meta-model is a declarative language to conceptualise an ABM. A model description in MAIA thus provides sufficient information to translate it into a simulation model – it defines the agents, their decision-making process and their actions, all within an institutional and physical context, to affect system states that are defined in the MAIA model. A modeller can use MAIA to specify and document her model and to build her simulation by using MAIA’s semi-automatic code generation option.@en

The modern world is dependent on complex evolving networks of production chains that convert raw resources into the products and services required for the functioning of society. Dealing with issues of the environmental sustainability of these systems can be difficult due to their large scale and dynamic nature. Understanding these systems requires large amounts of diverse data and proper information management techniques to help make sense of them. We propose a way forward based on Semantic Web standards, and illustrate the use of Semantic Wiki software to help facilitate a collaborative community process of gathering and managing this data, and enablingtransparent peer review of it. This type of system could greatly enablethe use of tools such as Life Cycle Analysis, which have very large data demands and have struggled to build larger databases, yet still maintain quality of the data.@en

Agent-based modeling is one of the popular tools for analyzing complex social systems. To model such systems, social attributes such as culture, law and institutions need to implemented as part of the context of a MAS, independently of individual agents. In this paper, we present MAIA; a framework for modeling agent-based systems based on the Institutional Analysis and Development Framework (IAD). The IAD is a well established comprehensive framework which addresses many social attributes. To make this framework applicable to agent-based software implementation, we inspire from some of the detailed definitions in the OperA methodology. The framework covers the different types of structures affecting agents at the operational level; physical, collective and constitutional. Moreover, this framework includes the conceptualization and design of evaluation. An agent-based methodology has also been developed from the MAIA framework which consists of two layers. A conceptualization layer for analyzing and decomposing the system and a detailed design layer which leads to the implementation of social models. MAIA allows the balance of global institutional requirements with the autonomy of individual agents thus enabling system evolution and reflecting more of reality in artificial societies.@en