SUPPORTING AGENT-ORIENTED MODELLING WITH UML

2002 ◽  
Vol 12 (06) ◽  
pp. 605-618 ◽  
Author(s):  
FEDERICO BERGENTI ◽  
AGOSTINO POGGI
Keyword(s):  
Software Engineering ◽  
Levels Of Abstraction ◽  
Uml Profile ◽  
Code Generator ◽  
Agent Platform ◽  
Level Of Abstraction ◽  
Agent Oriented Software Engineering ◽  
Development Framework ◽  
Interacting Agents ◽  
Multi Agent

Software engineering relies on the possibility of describing a system at different levels of abstraction. Agent-oriented software engineering introduces a new level of abstraction, that we called agent level, to allow the architect modelling a system in terms of interacting agents. This level of abstraction is not supported by an accepted set of tools and notations yet, even if a number of proposals are available. This paper introduces: (i) An UML-based notation capable of modelling a system at the agent level and (ii) A development framework, called ParADE, exploiting such a notation. The notation we propose is formalized in terms of a UML profile and it supports the realisation of artefacts modelling two basic concepts of the agent level, i.e., the architecture of the multi-agent system and the ontology followed by agents. The choice of formalising our notation in terms of a UML profile allows using it with any off-the-shelf CASE tool. The ParADE framework takes advantage of this choice by providing a code generator capable of producing skeletons of FIPA-compliant agents from XMI files of agent-oriented models. The developer is requested to complete the generated skeletons exploiting the services that ParADE and the underlying agent platform provide.

Social Structure Based Design Patterns for Agent-Oriented Software Engineering

2009 ◽  
pp. 773-796
Author(s):  
Manuel Kolp ◽  
Stéphane Faulkner ◽  
Yves Wautelet
Keyword(s):  
Software Engineering ◽  
Design Patterns ◽  
Autonomous Agents ◽  
Knowledge Bases ◽  
Multi Agent Systems ◽  
Business Systems ◽  
Agent Systems ◽  
Social Patterns ◽  
Agent Oriented Software Engineering ◽  
Multi Agent

Multi-agent systems (MAS) architectures are gaining popularity over traditional ones for building open, distributed, and evolving software required by today’s corporate IT applications such as e-business systems, Web services, or enterprise knowledge bases. Since the fundamental concepts of multi-agent systems are social and intentional rather than object, functional, or implementationoriented, the design of MAS architectures can be eased by using social patterns. They are detailed agent-oriented design idioms to describe MAS architectures composed of autonomous agents that interact and coordinate to achieve their intentions, like actors in human organizations. This article 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. We consider the Broker social pattern to illustrate the framework. An overview of the mapping from system architectural design (through organizational architectural styles), to system detailed design (through social patterns), is presented with a data integration case study. The automation of creating design patterns is also discussed.

The MESSAGE Methodology for Agent-Oriented Analysis and Design

2011 ◽  
pp. 203-235 ◽  
Author(s):  
Francisco J. Garijo ◽  
Jorge J. Gomez-Sanz ◽  
Philippe Massonet
Keyword(s):  
Software Engineering ◽  
Dynamic Environment ◽  
Multi Agent Systems ◽  
Detailed Design ◽  
Analysis And Design ◽  
Agent Oriented Software Engineering ◽  
Multi Agent ◽  
Unified Process ◽  
Design Case Study ◽  
High Level

This chapter presents the MESSAGE agent-oriented software engineering methodology and illustrates it in an analysis and design case study. The methodology covers MAS analysis and design and is intended for use in mainstream software engineering departments. MESSAGE integrates into a coherent AOSE methodology basic agent-related concepts (such as organisation, role, goal, interaction, and task) that have so far been studied largely in isolation. The MESSAGE notation extends the UML with agent knowledge-level concepts and diagrams with notations for viewing them. The proposed diagrams extend UML class and activity diagrams. TheMESSAGE analysis and design process is based on the Rational Unified Process (RUP). The methodology distinguishes high-level from detailed design. An organisation-driven approach is presented for detailed design, where the global architecture of the MAS is derived from the structure and behaviour of the organisations that interact. Experimentation with the methodology shows that it supports the analysis and design of multi-agent systems that are flexible and adapt to specific kind of changes in a heterogeneous and dynamic environment.

scholarly journals General Guidelines for Design of Affective Multi-Agent Systems

2017 ◽  
Vol 22 (1) ◽  
pp. 5-12 ◽  
Author(s):  
Māra Pudāne ◽  
Egons Lavendelis
Keyword(s):  
Software Engineering ◽  
Affective State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Agent Oriented Software Engineering ◽  
Traditional Design ◽  
Multi Agent ◽  
The Way

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.

Agent-oriented software engineering

2005 ◽  
Vol 20 (2) ◽  
pp. 99-116 ◽  
Author(s):  
CAROLE BERNON ◽  
MASSIMO COSSENTINO ◽  
JUAN PAVÓN
Keyword(s):  
Software Engineering ◽  
System Structure ◽  
Multi Agent Systems ◽  
Basic Definition ◽  
Specific Domain ◽  
Meta Model ◽  
Agent Oriented Software Engineering ◽  
Core Concepts ◽  
Multi Agent ◽  
Set Up

Considering the great number of agent-oriented methodologies that can be found in the literature, and the fact that each one defines its own concepts and system structure, one of the main challenges in agent-oriented software engineering (AOSE) research is how to make these methodologies interoperable. By defining concepts used in a specific domain in a non-ambiguous way, meta-modelling may represent a step towards such interoperability. Consequently the main objective of the AOSE TFG (Technical Forum Group) is to establish a strategy for identifying a common meta-model that could be widely adopted by the AOSE community. This paper sums up the approach used by this TFG which consists of (i) studying and comparing the meta-models related to some existing methodologies (ADELFE, Gaia, INGENIAS, PASSI, RICA and Tropos) in order to find commonalities and (ii) giving a clear and basic definition for the core concepts used in multi-agent systems for relating and positioning them in a unified MAS meta-model. The first proposal, set up by the working group, for this unified meta-model then concludes this paper.

Foundations for Knowledge and Belief Management

2021 ◽  
Vol 17 (3) ◽  
pp. 88-99
Author(s):  
Roderic A. Girle
Keyword(s):  
Intelligent Systems ◽  
Turing Test ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Conceptual Structures ◽  
Interacting Agents ◽  
Questions And Answers ◽  
Multi Agent ◽  
The Difference ◽  
Dialogue Theory

Three foundational principles are introduced: intelligent systems such as those that would pass the Turing test should display multi-agent or interactional intelligence; multi-agent systems should be based on conceptual structures common to all interacting agents, machine and human; and multi-agent systems should have an underlying interactional logic such as dialogue logic. In particular, a multi-agent rather than an orthodox analysis of the key concepts of knowledge and belief is discussed. The contrast that matters is the difference between the different questions and answers about the support for claims to know and claims to believe. A simple multi-agent system based on dialogue theory which provides for such a difference is set out.

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