An agent-based architecture for software tool coordination

International Journal on Software Tools for Technology Transfer, 2004

Tool integration is a very difficult challenge. Problems may arise at different abstraction levels and from several sources such as heterogeneity of manipulated data, incompatible interfaces, or uncoordinated services, to name just a few examples. On the other hand, applications based on the coherent composition of activities, components, services, and data from heterogeneous sources are increasingly present in our everyday lives. Consequently, tool integration takes on increasing significance.

There are many agent tools for facilitating professional programmers in developing multi-agent systems (MAS); however, not all of them can be easily used by users who are not professional programmers. Also there is a need for MAS to provide explicit support for agent cooperation. Therefore, in this paper we propose a script language to enable non-professionals to build their agents in an easy way using available tools and we implement a cooperative work support module which is based on the Agora concept. The developed platform is implemented as a plug-in to the JADE system; however, it can be also plugged-in to other agent platforms who comply with FIPA ACL.

Proceedings ITCC 2003. International Conference on Information Technology: Coding and Computing, 2003

Developing a knowledge-sharing capability across distributed heterogeneous data sources remains a significant challenge. Ontology-based approaches to this problem show promise by resolving heterogeneity, if the participating data owners agree to use a common ontology (i.e., a set of common attributes). Such common ontologies offer the capability to work with distributed data as if it were located in a central repository. This knowledge sharing may be achieved by determining the intersection of similar concepts from across various heterogeneous systems. However, if information is sought from a subset of the participating data sources, there may be concepts common to the subset that are not included in the full common ontology, and therefore are unavailable for knowledge sharing. One way to solve this problem is to construct a series of ontologies, one for each possible combination of data sources. In this way, no concepts are lost, but the number of possible subsets is prohibitively large. This paper describes a software agent case study that demonstrates a flexible and dynamic approach for the fusion of data across combinations of participating heterogeneous data sources to maximize knowledge sharing. The software agents generate the largest intersection of shared data across any selected subset of data sources. This ontology-based agent approach maximizes knowledge sharing by dynamically generating common ontologies over the data sources of interest. The approach was validated using data provided by five (disparate) national laboratories by defining a local ontology for each laboratory (i.e., data source). In this experiment, the ontologies are used to specify how to format the data using XML to make it suitable for query. Consequently, software agents are empowered to provide the ability to dynamically form local ontologies from the data sources. In this way, the cost of developing these ontologies is reduced while providing the broadest possible access to available data sources.

2003

With the rapid technological development particularly in the computer industry, many computer programming languages are being developed with many computer programs written in these languages. Writing good programs takes time and effort. It is therefore necessary that programs once written should be able to work together (interoperate) with each other so that a program written in one language can benefit from the advantages that may be associated with another program written in another language. One of the problems with interoperation of programs is the heterogeneity of the programs. This is because programs are written by different people, at different times, in different languages and with different interfaces. Agent-base Software Engineering is an attempt to facilitate the creation of software products that can easily interoperate in such settings. In Agent-base Software Engineering, programs are written as software agents (software components) that communicate with each other by exchanging messages through a communication language. For a successful communication in such heterogeneous environments, the agents have to share knowledge with each other. The aim of this tutorial is to discuss agent communication and knowledge sharing. A discussion about agent communication, methods of agent communication, agent communication languages, content languages and knowledge sharing between agents is presented together with constraints that may inhibit successful knowledge sharing and agent communication.

International Journal of Computer Applications, 2010

Software agent is the one of the most recent contribution in the field of Information Technology. The field of software agents is a broad and rapidly developing area of research, which encompasses a diverse range of topics and interests. In order to study the various methodologies for agent design, implementation, commercial use of it, a sample survey is required.

Artificial intelligence research and …, 2003

Cooperative Problem Solving is usually focused on the coordination and cooperation mechanisms of Multi-Agent Systems, leaving out the user and the problem requirements. This paper introduces the knowledge description level of ORCAS (Open, Reusable and Configurable multi-Agent Systems), a framework to develop MAS applications configurable on demand, according to problem requirements and user preferences. ORCAS introduces the idea of configuring a MAS application at two layers, the knowledge and the operational layers. During the knowledge layer a configuration of MAS components is found, including agent capabilities and domain knowledge; and after that the knowledge configuration is operationalized by a customized team of problem solving agents. This framework is based on applying a knowledge modelling approach to describe Multi-Agent Systems, specifically, it proposes to describe agent capabilities as Problem-Solving Methods.

1999

The development o f m ulti-agent systems on the Web requires powerful and e ective coordination models, languages and patterns. Even more, it calls for an e ective coordination technology, not only implementing a coordination model, but also supporting its metaphors at the development system level, and enabling developers to work at any time at the abstraction level required. This paper presents the LuCe coordination system for the development o f m ulti-agent systems on the WWW. Based on the full integration of Java and Prolog technologies, LuCe implements a coordination model based on the notion of logic tuple centre, a coordination medium which is also exploited as the core of the development system. The power of the LuCe coordination technology is rst discussed in general, then shown in the context of an application example, a TicTacToe game among intelligent software agents and human players on the Web.

Applied Artificial Intelligence, 2002

Development and deployment tools are required to effectively support the engineering of multi-agent systems (MAS). In particular, tools are needed to monitor and debug interagents aspects, such as interaction protocols, coordination policies and environment constraints. By assuming interaction as a firstclass issue, this paper aims at identifying the main aspects of support tools for an effective agent infrastructure, and takes tuple-based coordination infrastructures as its reference. The role of support tools is ...

During the design and development of multi-agent systems, all aspects related to interoperability among each of the individual agents, that form part of the distributed system, require special attention. This paper shows how communication agents facilitate the interoperability between the components of multi-agent systems. These agents are in charge of the communication between other agents. They increment the flexibility of distributed systems and facilitate the incorporation of new agents into such systems. A multi-agent advisory system is an example of an architecture of this type and it is presented in this paper.

2004

With the objective of defining the interoperability theme of this year’s conference it is the purpose of this paper1 to trace the evolution of intelligent software from data-centric applications that essentially encapsulate their data environment to ontology-based applications with automated reasoning capabilities. The author draws a distinction between human intelligence and component capabilities within a more general definition of intelligence; - a kind of intelligence that can be embedded in computer software. The primary vehicle in the quest for intelligent software has been the gradual recognition of the central role played by data and information, rather than the logic and functionality of the application. The three milestones in this evolution have been: the separation of data management from the internal domain of the application; the development of standard data exchange protocols such as XML that allow machine interpretable structure and meaning to be added to data exchan...

Today's enterprises must adapt their business processes to work in open settings, such as online marketplaces and, more generally, the Web, where business relationships exhibit a high degree of dynamism. Moreover, open settings are characterized by the autonomy and heterogeneity of the enterprises. In such settings, interoperability of / between the information systems that support and automate business processes and applications is a key concern: how do we ensure that diverse enterprises can work together towards a mutually desirable end? Interoperability problems occur at different levels: at the business level (how organizations do business together, what needs to be described and how?), at the knowledge level (different formats, schemas, and ontologies), and at the infrastructure level (the underlying information and communication technologies and systems). Agents, Model-Driven Architecture (MDA), and Service-Oriented Architecture (SOA) are complementary approaches to addressing the enterprise interoperability problem.

ABSTRACT The main problem addressed in this paper is the heavy-weighted processes involved in the dialogue management and knowledgebased tasks that support the user-agent interaction according with the user needs and the dialogue evolution. The approach followed in the deployed system has been a two-sided double communication solution, based on the different functionalities of the agents in either side, and the communication features offered by the programming languages involved (Ciao-Prolog and Java).

2000

is one of six departments that make up the School of Business at the University of Otago. The department offers courses of study leading to a major in Information Science within the BCom, BA and BSc degrees. In addition to undergraduate teaching, the department is also strongly involved in postgraduate research programmes leading to MCom, MA, MSc and PhD degrees. Research projects in spatial information processing, connectionist-based information systems, software engineering and software development, information engineering and database, software metrics, distributed information systems, multimedia information systems and information systems security are particularly well supported. The views expressed in this paper are not necessarily those of the department as a whole. The accuracy of the information presented in this paper is the sole responsibility of the authors. Copyright remains with the authors. Permission to copy for research or teaching purposes is granted on the condition that the authors and the Series are given due acknowledgment. Reproduction in any form for purposes other than research or teaching is forbidden unless prior written permission has been obtained from the authors. This paper represents work to date and may not necessarily form the basis for the authors' final conclusions relating to this topic. It is likely, however, that the paper will appear in some form in a journal or in conference proceedings in the near future. The authors would be pleased to receive correspondence in connection with any of the issues raised in this paper, or for subsequent publication details. Please write directly to the authors at the address provided below. (Details of final journal/conference publication venues for these papers are also provided on the Department's publications web pages: ). Any other correspondence concerning the Series should be sent to the DPS Coordinator.

1997

In today's open, distributed environments, there is an increasing need for systems to assist the interoperation of tools and information resources. This paper describes a multi-agent system, DALEKS, that supports such activities for the information processing domain. With this system, information processing tasks are accomplished by the use of an agent architecture incorporating task planning and information agent matchmaking components. We discuss the characteristics of planning in this domain and describe how information processing tools are specified for the planner. We also describe the manner in which planning, agent matchmaking, and information task execution are interleaved in the DALEKS system. An example application taken from the domain of university course administration is provided to illustrate some of the activities performed in this system.

Software agents became popular in the development of complex software systems, especially those requiring autonomous and proactive behavior. Agents interact with each other within a Multi-agent System (MAS), in order to perform certain defined tasks in a collaborative and/or selfish manner. However, the autonomous, proactive and interactive structure of MAS causes difficulties when developing such software systems. It is within this context, that the use of a Domain-specific Language (DSL) may support easier and quicker MAS development methodology. The impact of such DSL usage could be clearer when considering the development of MASs, especially those working on new challenging environments like the Semantic Web. Hence, this paper introduces a new DSL for Semantic Web enabled MASs. This new DSL is called Semantic web Enabled Agent Language (SEA_L). Both the SEA_L user-aspects and the way of implementing SEA_L are discussed in the paper. The practical use of SEA_L is also demonstrated using a case study which considers the modeling of a multi-agent based e-barter system. When considering the language implementation, we first discuss the syntax of SEA_L and we show how the specifications of SEA_L can be utilized during the code generation of real MAS implementations. The syntax of SEA_L is supported by textual modeling toolkits developed with Xtext. Code generation for the instance models are supplied with the Xpand tool.