RationalGRL: A Framework for Argumentation and Goal Modeling

Goal-oriented requirements modeling approaches aim at capturing intentions of various stakeholders involved in the development of an information system and refining them into low level goals and tasks. The process of constructing a goal model usually involves discussions between a requirements engineer and a group of stakeholders. While it is possible to capture part of this discussion process in a goal model, by specifying alternative solutions for a goal, not all of the arguments can be found back in the resulting model. For instance, the discussion on whether to accept or reject a certain goal and the ultimate rationale for acceptance or rejection cannot be captured in current goal modeling languages. In this paper, we apply argumentation techniques from artificial intelligence to a goal modeling approach by using a coding analysis in which stakeholders discuss requirements for a Traffic Simulator. We combine a simplified version of a traditional goal modeling approach, the Goal-oriented Requirements Language (GRL), with a formal Practical Reasoning Argument Scheme (PRAS) for reasoning about goals into a new framework (RationalGRL). RationalGRL provides a formal semantics and tool support to capture the discussions and outcomes of the argumentation process that leads to a goal model. We also define the RationalGRL development process to create a RationalGRL model.

• Machine Intelligence

• General Science