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  This page will provide the Web resources regarding the publications of multiple aspects of software agents research, such as introduction, design technology, languages, etc.

 

General Introduction

Agent theories, architecture and languages: a survey: This paper discussed the most important theoretical and practical issues associated with the design and construction of intelligent agents.  Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents. Agent languages are software systems for programming and experimenting with agents; these languages typically embody principles proposed by theorists. (By Michael J. Wooldridge, Dept. of Computing, Manchester Metropolitan University and Nicholas R. Jennings, Dept. of Electronic Engineering, Queen Mary & Westfield College) (PTF)

The Info Agent: an Interface for Supporting Users in Intelligent Retrieval: In this paper we present a system that supports users in retrieving data in distributed and heterogeneous archives and repositories. The architecture is based on the metaphor of the software agents and incorporates innovative hints from other fields: distributed architectures, relevance feedback and active interfaces. (By Daniela D'Aloisi and Vittorio Giannini, Fondazione Ugo Bordoni) (HTML)

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Agent Design & Architecture

Architecture-centric object-oriented design method for multi-agent system: This paper introduces an architecture-centric object-oriented design method for MAS (Multi-Agent Systems) using the extended UML (Unified Modeling Language). The UML extension is based on design principles that are derived from characteristics of MAS and concept of software architecture which helps to design reusable and well-structured multi-agent architecture. The extension allows one to use original object-oriented method without syntactic or semantic changes which implies the preservation of OO productivity, i.e., the availability of developers and tools, the utilization of past experiences and knowledge, and the seamless integration with other systems. (By Hongsoon Yim, Kyehyun Cho, Jongwoo Kim, and Sungjoo Park)  (PDF)

Analysis and design multi-agent system using MAS comonKADS: This article proposes an agent-oriented methodology called MAS-CommonKADS, which extends the knowledge engineering methodology CommonKADS with techniques from object-oriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, Task Model, Ex-pertise Model, Organisation Model, Coordination Model, Communication Model and Design Model. (By Carlos A. Lglesias, Mercedes Garijo ,Jos´ e C. Gonz´ alez and Juan R. Velasco) (PDF)

Agent orientated analysis using MESSAGE/UML: This paper presents the MESSAGE/UML agent oriented software engineering methodology and illustrates it on an analysis case study. The methodology covers MAS analysis and design and is intended for use in mainstream software engineering departments. MESSAGE extends UML by contributing agent knowledge level concepts, and diagrams with notations for viewing them. (By Giovanni Caire, Telecom Italia LAB; Francisco Leal, Paulo Chainho, PT Inovação and Richard Evans, Broadcom Eireann Research Ltd) (PDF)

Agent-Oriented Design: This paper proposed a functional decomposition of problem solving activities to serve as a framework to assist MAS designers in their selection and integration of different techniques and existing research results according to their system requirements and presented a proposed model for the domain of naval radar frequency management. (HTML)

A Survey of Cognitive and Agent Architectures: The paper provides some rational, structured access to an analysis of cognitive and agent architectures. Twelve architectures have been used for this preliminary analysis representing a wide range of current architectures in artificial intelligence (AI). The aim of the project is to facilitate both an understanding of current architectures and provide insight to the development of future, improved intelligent agent architectures. (HTML)

Using Ontologies in the multi-agent system: Multi-Agent System (MAS) architectural framework allows human and software agents to interoperate and thus cooperate within common application areas. Within a MAS, the different "views of the world" of knowledgeable agents are to be bridged through their commitment to common ontologies and terminologies. Ontology and terminology servers providing other agents with the common semantic foundation required for effective interoperation, and allowing the configuration of suitable application ontologies for distributed applications. (HTML)

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Agent Communication & Collaboration

Modeling, communication, and translation in the ACL project: This paper discusses three issues that are central to the ACL project, such as the necessity  to communicate the inheritance and constituency relationships, the Ontolingua, a system for creating portable ontologies comparing them to the CMU Object Model Specification Language and the translation of vocabulary. (By Taha Khedro, Daniel Malmer, Michael Genesereth, and Paul Teicholz, 1995) (HTML)

The Agent Collaboration Environment, an Assistant for Architects and Engineers: This Agent Collaboration Environment (ACE) provides the infrastructure for a community of cooperative agents to assist a team of users. In contrast to traditional blackboard systems, agents are organized into business processes to reflect differences in tasks and workflow between users from different disciplines and/or organizations. (HTML)

Cooperation-ware: integration of human collaboration with agent-based interaction: This paper presents a platform that integrates cooperation facilities for the most important types of interaction. Cooperation-Ware is a framework for integrating software components supporting all of the above types of communication. It includes audio/video conferencing and tele-pointing, data and application sharing, and agents as well as user agents. The functionality is based on a formal model specifying cooperative actions executed by humans or agents. (HTML)

Collaborative interface agent: This paper focus on the research on the Learning interface agents, which employ machine learning techniques to provide assistance to a user dealing with a particular computer application. The learning techniques achieved a level of personalization impossible with knowledge engineering, and without the user intervention required by rule-based systems. In order to address the problems of long "learning curve" of such techniques, a collaborative solution that experienced agents can help a new agent come up to speed quickly as well as help agents in unfamiliar situations was proposed. (HTML)

Coordination of multiple intelligent software agents: this paper investigated the techniques for developing distributed and adaptive collections of information agents that coordinate to retrieve, filter and fuse information relevant to the user, task and situation, as well as anticipate user's information needs, The paper also present  the distributed system architecture, agent collaboration interactions, and a reusable set of software components for structuring agents. (HTML)

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Agent-oriented Software Engineering

A framework for modeling agent-oriented software: This paper introduce an extension of G-Nets, agent-based G-Net, as a generic model for agent design, and progress from an agent-based design model to an agent-oriented model, new mechanisms to support inheritance modeling  In addition, an agent family in electronic commerce is provided in order to illustrate the formal modeling technique for multi-agent systems. (By Haiping Xu and Sol M. Shatz, Department of Electrical Engineering and Computer Science, The University of Illinois at Chicago) (PDF)

Agent-Oriented Software Engineering: This paper argued that the conceptual apparatus of agent-oriented systems was well-suited to building software solutions for complex systems and  agent-oriented approaches represent a genuine advance over the current state of the art for engineering complex systems. Based on view, the paper highlighted and discussed  the major issues raised by adopting an agent-oriented approach to software engineering. (By Nicholas R. Jennings, Michael Wooldridge, 2000. Proceedings of the 9th European Workshop on Modelling Autonomous Agents in a Multi-Agent World : Multi-Agent System Engineering (MAAMAW-99)) (PDF)

Determining When to Use an Agent-Oriented Software Engineering Paradigm: This paper discussed the approach to determine the criteria  and technique to assist software engineers to select appropriate software engineering methodology. (By Scott A. O’Malley 1 and Scott A. DeLoach 2001. Proceedings of the Second International Workshop On Agent-Oriented Software Engineering (AOSE-2001), Montreal, Canada, May 29th 2001.) (PDF)

Agent-Oriented Software Engineering: The State of the Art : This paper discussed that the intelligent agents and multi-agent system are the tools of software engineering, by reviewing what is meant by the term "agent". The paper also examined a number of  a number of prototype techniques proposed for engineering agent systems, including methodologies for agent-oriented analysis and design, formal specification and verification methods for agent systems, and techniques for implementing agent specifications. (By Michael Wooldridge, Paolo Ciancarini, 2000.)

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Agent Automation

Autonomy: specification, measurement, and dynamic adjustment: This paper introduced the definition of the autonomy of the agents, discuss the autonomy representation as well as the autonomy constraints. (HTML)

Modeling Adaptive Autonomous Agents: This paper extracts the main idea of the new approach of building adaptive autonomous agents in artificial intelligence research, evaluates its contributions, and identify its current limitations and open problems. (HTML)

IBHYS: A New Approach to Learn Users Habits: this paper introduces a new approach  which is particularly suited for learning interface agents because it provides an incremental algorithm with low training time and decision time, which does not require, from the designer of the interface agent, to de-scribe in advance and quite carefully the repetitive patterns searched. This approach limits the hypothesis search to a small portion of the hypothesis space by letting each training example build a local approximation of the global target function. (HTML)

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Agent Application

An application of intelligent and mobile agent in visual mining and e-commerce in the internet:  This paper present an agent-based system architecture for information retrieval and visualization on the Internet,  focusing on the development of a multi-agent-based problem-solving strategy. Important features of the architecture are the use of mobile agents as a device for searching and navigating through distributed data, and the ability to present results using visual techniques. (HTML)

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