Agent-oriented Software Engineering Research Articles

The ASEME methodology

In this paper, we present a complete view of an agent-oriented software engineering methodology called agent systems engineering methodology (ASEME). Several parts of the methodology concerning different aspects of the whole development process have already been published in the past in several papers. However, our goal in this paper is to provide a global view on the methodology by providing information about the agent (and multi-agent systems) development process along with recent works concerning the tools that we have developed in order to facilitate the use of ASEME by agent systems developers. We also provide some information on the different practical applications that we have developed using ASEME and which prove that ASEME is very well suited for the development of real world applications.

ADMINISTRATION AND MONITORING OF COMPUTER NETWORKS AS A METHOD OF SOLVING MODERN PROBLEMS IN FINANCIAL SYSTEMS

The article defines the role of administration and monitoring of computer networks in financial systems. The main objectives of monitoring are network activities. Research analysis and task setting are to monitor traffic as an important source of information for effective network management, bringing the main functions of network administrators in financial systems. The effectiveness of monitoring using network traffic analyzers depends on the topology of the network under study, its configuration, and the set of devices from which the network is built. The result of the study in the form of two main needs is monitoring and analysis. Effective network management in the field of finance and banking systems, as well as continuous improvement of software in financial systems. What are the requirements for software agent technology? The main functions and tasks of network administration - a description of monitoring, its tools and network analysis, which are divided into certain classes: protocol analyzers (Protocolanalyzers), system management tools (System Management), network management systems (Network Management Systems), built diagnostic and management systems (Embedded Systems), multifunctional devices for analysis and diagnostics, equipment for diagnostics and certification of cable systems, expert systems. The main functions of monitoring and analysis of network activity in financial systems are in the form of 4 items: performance analysis, network accounting, security management, error handling. The main aspects for the development of software for monitoring network activity, the needs that arise during the work with the network, the peculiarities of the administration of these networks, analyzed the existing software for monitoring network activity in financial systems. An example of the use of software for the administration and monitoring of computer networks is a description of the capabilities and highlighting the advantages and disadvantages of these programs in financial systems. This article discusses the following software: Total Network Monitor 2, Observium, Network Olympus, Zabbix.

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.

Simulation of connected driving in hazardous weather conditions: General and extensible multiagent architecture and models

Based on historical records, driving in hazardous weather conditions is one of the most serious causes that lead to fatal accidents on roads in general and in United Arab Emirates (UAE) highways in particular. One solution for improving road safety is to equip the vehicles and infrastructure with connected and smart devices. Before deploying a concrete solution to the field, it must be validated by simulation, and more specifically agent-based simulation. Several key features are expected for the simulation framework, such as the reproduction of different and detailed behaviors for the components of the road infrastructure and for the drivers, simulate specific weather conditions and forecast their impacts on the global system behavior. Additionally, several technological features are related to recent advancements in agent software engineering and simulation. This paper proposes an agent-based model for the modeling and simulation of traffic in foggy weather conditions that covers the above features and technological requirements. The architecture is used and validated on two scenarios of traffic on UAE highways in foggy weather conditions. The first scenario does not include an intelligent transport system, and the second considers smart speed limit panels. From the experiments, the proposed model supports the expected key features, i.e., microscopic simulation of intelligent transport systems, including infrastructure and connected cars, and of different driving behaviors (human or autonomous car). Even if the included weather condition model is basic, a proof of concept is provided regarding the connection of an agent model and a weather condition model.

A Repository of Method Fragments for Agent-Oriented Development of Learning-Based Edge Computing Systems

The upcoming avenue of IoT, with its massive generated data, makes it really hard to train centralized systems with machine learning in real time. This problem can be addressed with learning-based edge computing systems where the learning is performed in a distributed way on the nodes. In particular, this work focuses on developing multi-agent systems for implementing learning-based edge computing systems. The diversity of methodologies in agent-oriented software engineering reflects the complexity of developing multi-agent systems. The division of the development processes into method fragments facilitates the application of agent-oriented methodologies and their study. In this line of research, this work proposes a database for implementing a repository of method fragments considering the development of learning-based edge computing systems and the information recommended by the FIPA technical committee. This repository makes method fragments available from different methodologies, and computerizes certain metrics and queries over the existing method fragments. This work compares the performance of several combinations of dimensionality reduction methods and machine learning techniques (i.e., support vector regression, k-nearest neighbors, and multi-layer perceptron neural networks) in a simulator of a learning-based edge computing system for estimating profits and customers.

A knowledge-intensive adaptive business process management framework

Business process management has been the driving force of optimization and operational efficiency for companies until now, but the digitalization era we have been experiencing requires businesses to be agile and responsive as well. In order to be a part of this digital transformation, delivering new levels of automation-fueled agility through digitalization of BPM itself is required. However, the automation of BPM cannot be achieved by solely focusing on process space and classical planning techniques. It requires a holistic approach that also captures the social aspects of the business environment, such as corporate strategies, organization policies, negotiations, and cooperation. For this purpose, we combine BPM, knowledge-intensive systems and intelligent agent technologies, and yield one consolidated intelligent business process management framework, namely agileBPM, that governs the entire BPM life-cycle. Accordingly, agileBPM proposes a modeling methodology to semantically capture the business interests, enterprise environment and process space in accordance with the agent-oriented software engineering paradigm. The proposed agent-based process execution environment provides cognitive capabilities (such as goal-driven planning, norm compliance, knowledge-driven actions, and dynamic cooperation) on top of the developed business models to support knowledge workers’ multi-criteria decision making tasks. The context awareness and exception handling capabilities of the proposed approach have been presented with experimental studies. Through comparative evaluations, it is shown that agileBPM is the most comprehensive knowledge-intensive process management solution.

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.

Use of Software Agent Technology in Management Information System: A Literature Review and Classification

Technological innovations over the years have accentuated the workings in corporate- connected organizations and different application platforms. Hence, a unified management information system (MIS) that can utilize the Web and propel programming developments is required. Software agents, the latest developments in computer software technology, can be utilized to rapidly and effortlessly build integrated information systems. Consequently, 59 research papers on the use of software agents in MIS were identified from top 40 MIS journals published between 2007 and 2017. Then, we reviewed and classified all the research papers according to two categories: application fields and application categories. The application fields consisted of eight sub-groups: manufacturing, telecommunication systems, traffic and transportation management, information filtering and gathering, electronic commerce, business process management, entertainment, and medical care; whereas the application categories consisted of three sub-groups: multi-agent systems, personal assistants, and multi-agent simulation. The research papers were further divided into journal and year of publication, and journal and application field. The objective of our research was to understand the trend of the use software agent technology in MIS by examining the published research paper beside to add knowledge and content to the information system academic discipline.

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

In agent-oriented software engineering (AOSE), the application of model-driven development (MDD) and the use of domain-specific modeling languages (DSMLs) for Multi-Agent System (MAS) development are quite popular since the implementation of MAS is naturally complex, error-prone, and costly due to the autonomous and proactive properties of the agents. The internal agent behavior and the interaction within the agent organizations become even more complex and hard to implement when the requirements and interactions for the other agent environments such as the Semantic Web are considered. Hence, in this study, we propose a model-driven MAS development methodology which is based on a domain-specific modeling language (called SEA_ML) and covers the whole process of analysis, modeling, code generation and implementation of a MAS working in the Semantic Web according to the well-known Belief-Desire-Intention (BDI) agent principles. The use of new SEA_ML-based MAS development methodology is exemplified with the development of a semantic web-enabled MAS for electronic bartering (E-barter). Achieved results validated the generation and the development-time performance of applying this new MAS development methodology. More than half of the all agents and artifacts needed for fully implementing the E-barter MAS were automatically obtained by just using the generation features of the proposed methodology.

Validating MAS analysis models with the ASEME methodology

When designing agent-oriented software, engineers should consider performance-related non-functional requirements. To this end, performance engineering practices provide a useful toolbox. In particular, simulation of the system's processes appears eminently suitable. Agent-oriented software engineering methodologies are not directly linked to process simulation features. This paper extends an AOSE methodology for transforming agent roles models to process models, and for streamlining the transformation process towards simulation. Our method allows process model generation, aiming to support the process simulation, and was integrated into a model-driven engineering methodology. We used an established process modelling notation (BPMN) as the target language for the process model, and we are able to deliver a ready-to-simulate model. Through simulation, an analyst can validate specific system requirements and test scenarios of how the system scales beyond the current requirements. Furthermore, because of process models familiarity within the business domain, engineers, managers and stakeholders can seamlessly communicate system designs.

Validating MAS analysis models with the ASEME methodology

When designing agent-oriented software, engineers should consider performance-related non-functional requirements. To this end, performance engineering practices provide a useful toolbox. In particular, simulation of the system's processes appears eminently suitable. Agent-oriented software engineering methodologies are not directly linked to process simulation features. This paper extends an AOSE methodology for transforming agent roles models to process models, and for streamlining the transformation process towards simulation. Our method allows process model generation, aiming to support the process simulation, and was integrated into a model-driven engineering methodology. We used an established process modelling notation (BPMN) as the target language for the process model, and we are able to deliver a ready-to-simulate model. Through simulation, an analyst can validate specific system requirements and test scenarios of how the system scales beyond the current requirements. Furthermore, because of process models familiarity within the business domain, engineers, managers and stakeholders can seamlessly communicate system designs.

A Proposed Model of an Intelligent Software Agent for Marketing Education (ISAME)

The purpose of this article is to illustrate the advantages of intelligent software agent technologies in order to facilitate the location and customization of appropriate marketing education resources, as well as to foster collaboration between individuals within digital environments. In order to do this, this article discusses how such intelligent and interactive software can translate into a better educational environment for marketing curriculum, particularly e-marketing courses. The authors present a conceptual model for managing marketing training and education using intelligent software agent, based on extant literature. So, this article presents some initial test of the proposed model of ISAME usage in marketing education in e-marketing class.

Software development with Petri nets and agents: Approach, frameworks and tool set

Software development – especially of distributed and concurrent systems – requires sophisticated frameworks and tool support for the individual and collaborative development. We present an approach for the development of such systems, which applies concepts, technologies and techniques from agent and Petri net theory as well as from software engineering. The approach is backed by a set of elaborated frameworks and a powerful tool set. The Petri Net-based Agent-Oriented Software Engineering approach ( Paose ) follows the multi-agent paradigm and applies Petri net formalisms as implementation languages. Paose is a comprehensive approach that provides techniques, tools, methods, principles and defined processes. Paose depends on Mulan (Multi-Agent Nets), which is a conceptual framework for a multi-agent platform based on Petri net models. Mulan is modeled and executed in Renew (The Reference Net Workshop), which is an extensible modeling and execution environment for Reference Net-based systems and other modeling techniques. The whole framework landscape constitutes a Petri net IDE (Integrated Development Environment) that supports the development and execution of concurrent and distributed multi-agent systems. The Reference Net formalism includes concepts such as net instances (object-orientation), synchronous channels (communication/synchronization) and a seamless Java integration. In this contribution we present an overview of the frameworks and the tool sets in the context of the Paose approach. We focus in detail on the highlights and the IDE features of Renew , without which the collaborative development of distributed Paose -based software would not be feasible.

Development of a Graphical Tool to integrate the Prometheus AEOlus methodology and Jason Platform

Software Engineering (SE) is an area that intends to build high-quality software in a systematic way. However, traditional software engineering techniques and methods do not support the demand for developing Multiagent Systems (MAS). Therefore a new subarea has been studied, called Agent Oriented Software Engineering (AOSE). The AOSE area proposes solutions to specific issues related to the development of agent oriented systems. There are several methodologies to model MAS, however, until now, there is not a standard modelling language because they are very complex systems, and involve several different concepts. Another issue of this subarea is that there are very few tools that are able to automatically generate code, reducing its acceptance in the software development market. In this work, we propose a tool to support the Prometheus AEOlus Methodology, because it provides modelling artifacts to all MAS dimensions proposed by ~Demazeau: agents, environment, interactions and organization. The tool supports all Prometheus AEOlus artifacts and it can automatically generated code to the agent and interaction dimensions in the AgentSpeak(L) language, which is the language used in the Jason platform. We have done some validations with the proposed tool and a case study is presented. Our results indicate that our tool has full compatibility with the Jason platform, and it is able to automatic generate code in AgentSpeak(L). As future work, we intend to develop the integration of the artifacts with the JaCaMo framework, enabling a full integration between our tool and the Prometheus AEOlus methodology.

General Guidelines for Design of Affective Multi-Agent Systems

Abstract 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.

Model-driven engineering of multi-agent systems based on ontologies

Model-driven engineering provides abstractions and notations for improving the understanding and for supporting the modelling, coding, and verification of applications for specific domains. Ontologies, on the other hand, provide formal and explicit definitions of shared conceptualisations and enable the use of semantic reasoning. Although these areas have been developed by different communities, important synergies can be achieved when both are combined. These advantages can be explored in the development of multi-agent systems, given their complexity and the need for integrating several components that are often addressed from different angles. This work investigates how to apply ontologies for agentoriented software engineering. Initially, we present a new modelling approach where multiagent systems are designed using the proposed OntoMAS ontology. Then, we describe techniques, implemented in a tool, to help programmers bring their concepts into code and also generate code automatically from instantiated ontology models. Several advantages can be obtained from these new approaches to model and code multi-agent systems, such as semantic reasoning to carry out inferences and verification mechanisms. But the main advantage is the unified high (knowledge) level specification language that allows modelling the three dimensions that are united in the JaCaMo framework so that systems specifications can be better communicated across developing teams. The evaluations of these proposals indicate that they contribute with the different aspects of agent-oriented software engineering, such as the specification, verification, and programming of these systems.

Development of a Graphical Tool to integrate the Prometheus AEOlus methodology and Jason Platform

Software Engineering (SE) is an area that intends to build high-quality software in a systematic way. However, traditional software engineering techniques and methods do not support the demand for developing Multiagent Systems (MAS). Therefore a new subarea has been studied, called Agent Oriented Software Engineering (AOSE). The AOSE area proposes solutions to issues related to the development of agent oriented systems. There is still no standardization in this subarea, resulting in several methodologies. Another issue of this subarea is that there are very few tools that are able to automatically generate code. In this work we propose a tool to support the Prometheus AEOlus Methodology because it provides modelling artifacts to all MAS dimensions: agents, environment, interaction, and organization. The tool supports all Prometheus AEOlus artifacts and can automatically generated code to the agent and interaction dimensions in the AgentSpeak Language, which is the language used in the Jason Platform. We have done some validations with the proposed tool and a case study is presented.

Enabling Autonomic Computing Support for the JADE Agent Platform

Engineering complex distributed system is a real challenge documented in recent literature. Novel paradigms such as Autonomic Computing (AC) approaches appear to be the fittest engineering model in order to face performance instabilities of systems inserted in open and non-deterministic environments. To this purpose, the availability of appropriate development environments will facilitate the design of such systems. Standard agent development platforms represent a good starting point, but they generally lack of rigorous ways to define central AC-related concepts such as the prominent role of feedback loops and knowledge integration in decision making processes: we therefore believe that Agent Oriented Software Engineering (AOSE) can be substantially enriched by taking into account such concepts. In this paper, a novel extension of the well-known JADE agent development environment is discussed. This extension enhances JADE in order to address the engineering process with Autonomic Computing support. It is called Autonomic Computing Enabled JADE or shortly ACE-JADE. The behavioral model of ACE-JADE will be thoroughly described in the context of a case study (NASA ANTS project).

Centering ontologies in agent oriented software engineering processes

A plethora of Multi Agent Systems (MAS) development methodologies exists and all compete for prominence. This paper advocates unification of best of breed activities from these methodologies and examines two existing approaches for unifying access to them. It proposes an alternative approach that focusses on the use of domain knowledge through ontologies as offering the best potential for unifying access to them. The reliance on ontologies will provide flexibility in the process and workproducts use within the methodology. The focus on domain knowledge will reduce the number of mandatory methodological tasks and at the same time create scope for reuse with respect to both system designs and components. The paper will further sketch and argue for a full software development lifecycle for MAS where ontologies expressing domain knowledge are the central artifacts.