Modelling Frameworks

The success of the software system is measured by the degree to which it meets the purpose for which it was intended. Requirement Engineering is the process of discovering that purpose, by identifying stakeholders and their needs and documenting these in a form that is amendable to analysis, communication and implementation. Agent-oriented concepts are becoming very popular in software engineering as modelling frameworks for requirement engineering. This paper introduces the current Agent Oriented Requirement Engineering (AORE) Methodologies. It discusses what approaches have been followed; the suitability of these approaches for agent modelling; compares these approaches in a tabular form and some conclusions drawn from review.

There is growing interest in creating empirically grounded agent based models (ABMs) to simulate land use change at a variety of spatio-temporal scales. The development of land use change models is challenging, as there is a need to connect representations of human behavioural processes to simulations of the biophysical environment. This paper presents a new agent-based modelling framework (Aporia) that has the goal of reducing the complexity and difficulty of constructing high-fidelity land use models. Building on earlier conceptual developments for modelling land use change and the provision of ecosystem services, Aporia was designed to be modular, flexible and open, using a declarative, compositional approach to create complex models from subcomponents. The framework can be tightly or loosely coupled with multiple vegetation models, it can be set up to evaluate a range of ecosystem service indicators, and it can be calibrated for a range of different landscape-scale case studies and modelling styles. The framework is released under an Open Source licence, and can be freely re-used and modified to form the basis of new models. We illustrate this with two case studies implemented using Aporia, exploring different socioeconomic scenarios and behavioural characteristics on the land use decisions of Swiss and Scottish farmers. We also discuss the benefits of frameworks in terms of their flexibility, expandability, verification and transparency.

We discuss the motivations for, and software design concepts underpinning, the development of a regional water quality model. The Environmental Management Support System (EMSS) was developed to predict daily fluxes of runoff, total suspended sediment, total nitrogen and total phosphorous through a large-scale river network. It was built using a custom environmental modelling framework called Tarsier, founded on the Borland C++ Builder rapid application development environment. Three autonomous models are integrated within the EMSS, but are loosely coupled so that alternative models could be retrofitted into the system if desired. The three models share common data handling and visualisation routines resident in the Tarsier modelling environment and used in other modelling applications. The EMSS was designed for use by a range of stakeholders with varying levels of computer and technical proficiency. To satisfy their varying needs, we built three different interfaces, suited to 'expert', 'intermediate' and 'basic' users. The interfaces for the latter two groups were developed using interface prototyping methods, resulting in software that suited the user requirements. The object-oriented design employed in the coding of the EMSS has enhanced the extendibility and re-useability of the software. The EMSS development was part of a larger hydrologic modelling initiative aimed at reducing duplication in model building and standardising approaches to model design and delivery. The lessons learned during development of the EMSS have informed our future model development strategy.

There is growing interest in creating empirically grounded agent based models (ABMs) to simulate land use change at a variety of spatio-temporal scales. The development of land use change models is challenging, as there is a need to connect representations of human behavioural processes to simulations of the biophysical environment. This paper presents a new agent-based modelling framework (Aporia) that has the goal of reducing the complexity and difficulty of constructing high-fidelity land use models. Building on earlier conceptual developments for modelling land use change and the provision of ecosystem services, Aporia was designed to be modular, flexible and open, using a declarative, compositional approach to create complex models from subcomponents. The framework can be tightly or loosely coupled with multiple vegetation models, it can be set up to evaluate a range of ecosystem service indicators, and it can be calibrated for a range of different landscape-scale case studies and modelling styles. The framework is released under an Open Source licence, and can be freely re-used and modified to form the basis of new models. We illustrate this with two case studies implemented using Aporia, exploring different socioeconomic scenarios and behavioural characteristics on the land use decisions of Swiss and Scottish farmers. We also discuss the benefits of frameworks in terms of their flexibility, expandability, verification and transparency.

During the past decade a number of modelling frameworks for knowledge based systems have been developed. In this paper an approach to the comparison of modelling frameworks is proposed, based on the aims and purposes behind the frameworks. A purpose oriented comparison of the frameworks DESIRE, CommonKADS, PROTÉGÉ-II, MIKE, VITAL and KARL provides insight in their differences and similarities.

Land use change has an impact on regional sustainability which can be assessed using social, economic and environmental indicators. Stakeholder engagement tools provide a platform that can demonstrate the possible future impacts land use change may have to better inform stakeholder groups of the impact of policy changes or plausible climatic variations. To date some engagement tools are difficult to use or understand and lack user interaction whilst other tools demonstrate model environments with a tightly coupled user interface, resulting in poor performance. The research and development described herein relates to the development and testing of a visualisation engine for rendering the output of an Agent Based Model (ABM) as a 3D Virtual Environment via a loosely-coupled data driven communications protocol called Protocol Buffers. The tool, named Rural Sustainability Visualisation Tool (R.S.V.T) is primarily aimed to enhance nonexpert knowledge and understanding of the effects of l...

There is growing interest in creating empirically grounded agent based models (ABMs) to simulate land use change at a variety of spatio-temporal scales. The development of land use change models is challenging , as there is a need to connect representations of human behavioural processes to simulations of the biophysical environment. This paper presents a new agent-based modelling framework (Aporia) that has the goal of reducing the complexity and difficulty of constructing high-fidelity land use models. Building on earlier conceptual developments for modelling land use change and the provision of ecosystem services, Aporia was designed to be modular, flexible and open, using a declarative, compo-sitional approach to create complex models from subcomponents. The framework can be tightly or loosely coupled with multiple vegetation models, it can be set up to evaluate a range of ecosystem service indicators, and it can be calibrated for a range of different landscape-scale case studies and modelling styles. The framework is released under an Open Source licence, and can be freely re-used and modified to form the basis of new models. We illustrate this with two case studies implemented using Aporia, exploring different socioeconomic scenarios and behavioural characteristics on the land use decisions of Swiss and Scottish farmers. We also discuss the benefits of frameworks in terms of their flexibility, expandability, verification and transparency.