Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences

The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.

A Model of Normative Power

A power describes the ability of an agent to act in some way. While this notion of power is critical in the context of organisational dynamics, and has been studied by others in this light, it must be constrained so as to be useful in any practical application. In particular, we are concerned with how power may be used by agents to govern the imposition and management of norms, and how agents may dynamically assign norms to other agents within a multi-agent system. We approach the problem by defining a syntax and semantics for powers governing the creation, deletion, or modification of norms within a system, which we refer to as normative powers. We then extend this basic model to accommodate more general powers that can modify other powers within the system, and describe how agents playing certain roles are able to apply powers, changing the system’s norms, and also the powers themselves. We examine how the powers found within a system may change as the status of norms change, and show how standard norm modification operations — such as the derogation, annulment and modification of norms— may be represented within our system.

Automating the product derivation process of multi-agent systems product lines

Agent-oriented software engineering and software product lines are two promising software engineering techniques. Recent research work has been exploring their integration, namely multi-agent systems product lines (MAS-PLs), to promote reuse and variability management in the context of complex software systems. However, current product derivation approaches do not provide specific mechanisms to deal with MAS-PLs. This is essential because they typically encompass several concerns (e.g., trust, coordination, transaction, state persistence) that are constructed on the basis of heterogeneous technologies (e.g., object-oriented frameworks and platforms). In this paper, we propose the use of multi-level models to support the configuration knowledge specification and automatic product derivation of MAS-PLs. Our approach provides an agent-specific architecture model that uses abstractions and instantiation rules that are relevant to this application domain. In order to evaluate the feasibility and effectiveness of the proposed approach, we have implemented it as an extension of an existing product derivation tool, called GenArch. The approach has also been evaluated through the automatic instantiation of two MAS-PLs, demonstrating its potential and benefits to product derivation and configuration knowledge specification.