Agent-Oriented Software Engineering Methodologies: Analysis and Future Directions

The Internet of Things (IoT) facilitates in building cyber-physical systems, which are significant for Industry 4.0. Agent-based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. Yet a comprehensive and full-fledged agent approach for developing related projects is still lacking despite the presence of agent-oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object-oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.

Design Patterns for Social Intelligent Agent Architectures Implementation

Multi-agent systems (MAS) architectures are popular for building open, distributed, and evolving software required by today's business IT applications such as e-business systems, web services, or enterprise knowledge bases. Since the fundamental concepts of MAS are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions like actors in human organizations. This chapter presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. The authors consider the broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study.

Adding Emotions to Models in a Viewpoint Modelling Framework From Agent-Oriented Software Engineering

In modern software development, considering the viewpoints of stakeholders is an important step in building the right system. Over the past decade, several authors have proposed solutions to capture and model these viewpoints. While these solutions have been successful, emotions of stakeholders have been largely ignored. Considering the emotional needs of stakeholders is important because both the users' perceptions of a product and their use of a product are influenced by emotion as much as cognition. Building on recent work in modelling the emotional goals of stakeholders, the authors extend an existing viewpoint framework to capture emotions, and to use emotions in models from early-phase requirements to detailed software design. They demonstrate the models and framework with a case study of an emergency alarm system for older people, presenting a complete set of models for the case study. The authors introduce recent experience in using emotional models in requirements elicitation within an agile process.

BDI Agent Architectures: A Survey

The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach.

A Context-Aware and Self-Adaptation Strategy for Cloud Service Selection and Configuration in Run-Time

Day after day, the number of mobile applications deployed on cloud computing continues in increasing because of smartphone capabilities improvement. Cloud computing has already succeeded in the web-based application, for that reason, the demand for context-aware services provided by cloud computing increases. To customize a cloud service that takes into account the consumer requirements, which depend on information change, it brings to light many recent challenges to cloud computing about environment-aware, location-aware, time-aware. The cloud provider, moreover, has to manage personalized applications and the constraints of mobile devices in matters of interaction abilities and communication restrictions. This paper proposes a strategy for selecting automatically an appropriate cloud environment that runs out whole requirements, defines a configuration for the associated cloud environment and able to easily adapt to the change of the environment on either the user or the cloud side or both. This process builds on the principles of dynamic software product lines, Agent-oriented software engineering, and the MAPE-k model to select and configure cloud environments according to the consumer needs and the context change.

Adding Emotions to Models in a Viewpoint Modelling Framework From Agent-Oriented Software Engineering

In modern software development, considering the viewpoints of stakeholders is an important step in building the right system. Over the past decade, several authors have proposed solutions to capture and model these viewpoints. While these solutions have been successful, emotions of stakeholders have been largely ignored. Considering the emotional needs of stakeholders is important because both the users' perceptions of a product and their use of a product are influenced by emotion as much as cognition. Building on recent work in modelling the emotional goals of stakeholders, the authors extend an existing viewpoint framework to capture emotions, and to use emotions in models from early-phase requirements to detailed software design. They demonstrate the models and framework with a case study of an emergency alarm system for older people, presenting a complete set of models for the case study. The authors introduce recent experience in using emotional models in requirements elicitation within an agile process.

Design Patterns for Social Intelligent Agent Architectures Implementation

Multi-agent systems (MAS) architectures are popular for building open, distributed, and evolving software required by today's business IT applications such as e-business systems, web services, or enterprise knowledge bases. Since the fundamental concepts of MAS are social and intentional rather than object, functional, or implementation-oriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures as composed of autonomous agents that interact and coordinate to achieve their intentions like actors in human organizations. This chapter presents social patterns and focuses on a framework aimed to gain insight into these patterns. The framework can be integrated into agent-oriented software engineering methodologies used to build MAS. The authors consider the broker social pattern to illustrate the framework. The mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is overviewed with a data integration case study.

General Guidelines for Design of Affective Multi-Agent Systems

The paper presents general guidelines for designing affective multi-agent systems (affective MASs). The guidelines aim at extending the existing agent-oriented software engineering (AOSE) methodologies to enable them to design affective MASs. The reason why affective mechanisms need specific attention during the design is the fact that the way how both rational tasks and interactions are done differ based on the affective state of the agents. Thus, the paper extends the traditional design approaches with the design of affective mechanisms and includes them in the design of the system as a whole.

An Approach to Generate Software Agents for Health Data Mining

Data mining is a hot topic that attracts researchers of different areas, such as database, machine learning, and agent-oriented software engineering. As a consequence of the growth of data volume, there is an increasing need to obtain knowledge from these large datasets that are very difficult to handle and process with traditional methods. Software agents can play a significant role performing data mining processes in ways that are more efficient. For instance, they can work to perform selection, extraction, preprocessing, and integration of data as well as parallel, distributed, or multisource mining. This paper proposes a framework based on multiagent systems to apply data mining techniques to health datasets. Last but not least, the usage scenarios that we use are datasets for hypothyroidism and diabetes and we run two different mining processes in parallel in each database.