From SMART to agent systems development

n order for agent-oriented software engineering to prove effective it must use principled notions of agents and enabling specification and reasoning, while still considering routes to practical implementation. This paper deals with the issue of individual agent specification and construction, departing from the conceptual basis provided by the smart agent framework. smart offers a descriptive specification of an agent architecture but omits consideration of issues relating to construction and control. In response, we introduce two new views to complement smart: a behavioural specification and a structural specification which, together, determine the components that make up an agent, and how they operate. In this way, we move from abstract agent system specification to practical implementation. These three aspects are combined to create an agent construction model, actsmart, which is then used to define the AgentSpeak(L) architecture in order to illustrate the application of actsmart.

Prototype Generation from Ontology Charts

Semantic Analysis is a business analysis method designed to capture system requirements. While these requirements may be represented as text, the method also advocates the use of Ontology Charts to formally denote the system's required roles, relationships and forms of communication. Following model driven engineering techniques, Ontology Charts can be transformed to temporal Database schemas, class diagrams and component diagrams, which can then be used to produce software systems. A nice property of these transformations is that resulting system design models lend themselves to complicated extensions that do not require changes to the design models. For example, resulting databases can be extended with new types of data without the need to modify the database schema of the legacy system. Semantic Analysis is not widely used in software engineering, so there is a lack of experts in the field and no design patterns are available. This make it difficult for the analysts to pass organizational knowledge to the engineers. This study describes an implementation that is readily usable by engineers, which includes an automated technique that can produce a prototype from an Ontology Chart. The use of such tools should enable developers to make use of Semantic Analysis with minimal expertise of ontologies and MDA.

PrIMe: A Methodology for Developing Provenance-Aware Applications

Provenance refers to the past processes that brought about a given (version of an) object, item or entity. By knowing the provenance of data, users can often better understand, trust, reproduce, and validate it. A provenance-aware application has the functionality to answer questions regarding the provenance of the data it produces, by using documentation of past processes. PrIMe is a software engineering technique for adapting application designs to enable them to interact with a provenance middleware layer, thereby making them provenance-aware. In this article, we specify the steps involved in applying PrIMe, analyse its effectiveness, and illustrate its use with two case studies, in bioinformatics and medicine.

Dynamically Adapting BDI Agent Architectures based on High-level User Specifications

Users are facing an increasing challenge of managing information and being available anytime anywhere, as the web exponentially grows. As a consequence, assisting them in their routine tasks has become a relevant issue to be addressed. In this paper, we introduce a software framework that supports the development of Personal Assistance Software (PAS). It relies on the idea of exposing a high level user model in order to increase user trust in the task delegation process as well as empowering them to manage it. The framework provides a synchronization mechanism that is responsible for dynamically adapting an underlying BDI agent-based running implementation in order to keep this high-level view of user customizations consistent with it.

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.