Goal-and agent-oriented models have become a consolidated type of artifact in various software and knowledge engineering activities. Several languages exist for representing such type of models but there is a lack of associated methodologies for guiding their construction up to the necessary level of detail. In this paper we present RiSD, a method for building Strategic Dependency (SD) models in the i * notation. RiSD is defined in a prescriptive way to reduce uncertainness when constructing the model. RiSD tackles three fundamental issues: (1) it tends to reduce the average size of the resulting models; (2) it defines some traceability relationships among model elements; (3) it provides some lexical and syntactical conventions. As a result, we may say that RiSD supports the construction process of goal-and agent-oriented models whilst increasing their understanding.
i* is a widespread framework in the software engineering field that supports goal-oriented modeling of socio-technical systems and organizations. At its heart lies a language offering concepts such as actor, dependency, goal and decomposition. i* models resemble a network of interconnected, autonomous, collaborative and dependable strategic actors. Around this language, several analysis techniques have emerged, e.g. goal satisfaction analysis and metrics computation. In this work, we present a consolidated version of the i* language based on the most adopted versions of the language. We define the main constructs of the language and we articulate them in the form of a metamodel. Then, we implement this version and a concrete technique, goal satisfaction analysis based on goal propagation, using ADOxx. Throughout the chapter, we used an example based on open source software adoption to illustrate the concepts and test the implementation.
The i* (i-star) framework has been widely adopted by the information systems community. Since the time it was proposed, different variations have arisen. Some of them just propose slight changes in the language definition, whilst others introduce constructs for particular usages. This flexibility is one of the reasons that makes i* attractive, but it has as counterpart the impossibility of automatically porting i* models from one context of use to another. This lack of interoperability makes difficult to build a repository of models, to adopt directly techniques defined for one variation, or to use i* tools in a feature-oriented instead of a variant-oriented way. In this paper, we explore in more detail the interoperability problem from a metamodel perspective. We analyse the state of the art concerning variations of the i* language, from these variations and following a proposal from Wachsmuth, we define a supermetamodel hosting identified variations, general enough so as to embrace others yet to exist. We present a translation algorithm oriented to semantic preservation and we use the XML-based iStarML interchange format to illustrate the interconnection of two tools.
Goal-oriented and agent-oriented modelling provides an effective approach to the understanding of distributed information systems that need to operate in open, heterogeneous and evolving environments. Frameworks, firstly introduced more than ten years ago, have been extended along language variants, analysis methods and CASE tools, posing language semantics and tool interoperability issues. Among them, the i* framework is one the most widespread. We focus on i*-based modelling languages and tools and on the problem of supporting model exchange between them. In this paper, we introduce the i* interoperability problem and derive an XML interchange format, called iStarML, as a practical solution to this problem. We first discuss the main requirements for its definition, then we characterise the core concepts of i* and we detail the tags and options of the interchange format. We complete the presentation of iStarML showing some possible applications. Finally, a survey on the i* community perception about iStarML is included for assessment purposes.
There is a recognized lack of Agent Oriented Methodologies to translate a detailed design to a software implementation; here we address this problem with a solution approach. Tropos is one of the most used methodologies to design agent systems and we use it to show a design for the Food Collecting Agent Problem. Our solution includes autonomous behaviour, beliefs, multiple roles playing, communication and cooperation in a simple way. We propose a method to generate a Prolog implementation from a Tropos detailed design, adding a step allowing relevant decisions being incorporated at design time. Besides we show how to get the Prolog implementation from this detailed design. Our experience shows that this proposal is an intuitive, direct and effective way to get a Prolog implementation for an agent system. We end the paper with illustrations about our collecting team in action.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.