An Architecture and System for Support of Cooperation in Multi-Agent Software Development

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1 296 Conf. on Software Eng. Research and Practice SERP'07 An Architecture and System for Support of Cooperation in Multi-Agent Software Development Xuetao Niu, School of Information and Communication Technology Royal Institute of Technology Stockholm, Sweden Boxun Zhang School of Information and Communication Technology Royal Institute of Technology Stockholm, Sweden Mihhail Matskin Royal Institute of Technology Stockholm, Sweden and Norwegian University of Science and Technology, Norway Abstract - 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. Keywords: software agents, multi-agent systems, agentoriented software engineering. 1 Introduction Many customers and application developers accept agents [9,14] as an interesting, natural and promising paradigm for software development. However, there is no total agreement on which tools, platforms and infrastructures can be used for implementing agent-based systems. This is not only because of agent-based tools are not enough standardized yet but also because of a great variety of requirements from agent systems developers who may need tools of various levels. There has been developed many different solutions to multi-agent architectures [1,3,5,10,11,16,17,18,19]. One way to classify these architectures is by levels of their abstraction. Low level architectures usually focus on particular ways to create cooperative solutions, like e.g. the blackboard model [2,6]. On the other hand there are high level architectures that focus on mental states, like e.g. the BDI-architectures [4,12]. There is also a great variety of possible levels in between. We think that software infrastructure for multi-agent systems may be classified as a middleware which should support for MAS architectures of different levels. From this perspective an infrastructure for MAS may consist of different components. Some possible components of the infrastructure could be as follows: Communication support (including agent naming and messages routing) Protocols support (for example, negotiation, coordination protocols etc.) Agent machinery support (generic agent structure/architecture support) Cooperative work support (introducing cooperation nodes into MAS) Functional components (planner, knowledge base etc.) There are many agent systems for facilitating professional programmers in developing multi-agent systems; however, not all of them can be used by users who are not professional programmers. Also there are not many MAS that explicitly support agent cooperation and coordination. Therefore, in this paper, we propose a script language to enable non-professionals to build their agents easier using available tools and we implement a cooperative work support module which is based on the Agora concept. The script language provides most of agent-related operations while keeping a level of complexity lower than, for example, Java or C++. This language is also well-suited for automated generation of plans and actions. We design and implement an interpreter for the scripts. The interpreter allows integration of Action-Files implemented in different languages and this makes Plan-File scripts extensible. In order to support cooperative work we implement a generic Agora framework that supports agent negotiation and cooperation. Working on this architecture and system we took into account lessons learned during implementation and exploitation of the previous version of the Agora system [8]. The rest of the paper is organized as follows. First we describe the Agora concept. Then we overview Plan-files, Action-files and Interpreter. After that we briefly consider an example of Virtual Shopping Mall as an illustration of usage of Agora-based infrastructure. Finally we summarize our results and indicate some future work. 2 The Agora concept The idea of the agents co-operative work support in our system is based on concept of Agora [7,8]. Agora is a cooperative node where agents can register their interests, such as, skills, tasks they can perform and tasks they are

2 Conf. on Software Eng. Research and Practice SERP' interested in, working context, common knowledge etc. We came to the idea of Agora via analysis of a representative set of generic scenarios [7] of cooperative work. According to this analysis we consider a cooperative work in MAS as a set of communication, coordination and negotiation acts between participants (agents). We call such communication, coordination and negotiation acts as co-operative points. Using this terminology anytime we have a cooperative work we can identify participants and cooperative points in such work. In this case support of cooperative work assumes identification of cooperative points between participants in the cooperative work and providing infrastructure for these cooperative points. Such infrastructure is provided by Agoras. In other words Agora can be considered as a facilitator of cooperative work which 1) manages a proper protocol for negotiation and coordination, 2) constraints a context for negotiation, coordination and communication, 3) presents a template of situation for cooperative work Each Agora contains registered and default agents. The registered agents represent participants of cooperative activity and default agents correspond to management, service and matchmaking agents which are created by default when a new Agora is generated. The default agents can be redefined/overridden by the customer when needed. Agents can be registered at several Agoras and there could be interrelations between Agoras. 3 Architecture overview The Agora Platform is a distributed platform that facilitates the cooperative work among agents. It includes the following parts: A distributed agent runtime system which provides the agent communication support. Libraries which provide Agora-related and agentrelated functionalities. A graphical user interface which support deployment and monitoring agents and Agoras in the Agora Platform. Agora Agora Agent Agora Platform Distributed agent runtime (JADE) Network Layer Figure 1 Agora Platform distributes over several machines Figure 1 illustrates the Agora Platform distributed over different machines. The Agora Platform s functionality can be divided into two categories (see Figure 2): Agora management: this category includes deploying of Agoras, deploying of agents and destroying of existing Agoras and agents. Agora monitoring: functionalities in this category include monitoring group information of local and surrounding Agoras. Agora Host Host Host Agent Figure 2: Architecture of the Agora Platform

3 298 Conf. on Software Eng. Research and Practice SERP'07 The synchronization component provides functions to synchronize information between several Agora Platforms. The Plan-File support component provides support for the Plan-File scripts. 4 Plan-file System support provided in environments like JADE [15] assumes that its users are programmers. This allows efficient implementation of agent applications. However, there is a large group of non-professional programmers who have difficulties to use programming languages like JAVA and C++, while having experience in using Web and have a knowledge of markup languages. In order to target this group, we design Plan-File script language based on XML. All the tags supported in Plan-File script have clear meanings, which is easy for non-professional users to remember. In addition, Plan-File script supports weak-type variables and users do not need to pay too much attention to variable declarations and type conversions. Essentially, Plan-Files are scripts that all agents execute and each agent in our system has a Plan-File. In order to meet the requirements of most scenarios, Plan-File script supports five primitive types (Boolean, Long, Double, String and DateTime) and two complex types (Array and Structure). Plan-File script supports several control flow types (ifelse branch structure, while and for-each loop), expressions and in-script functions. In-script functions allow users to define their own functions in Plan-File scripts. This makes the script reusable and gives more clear script structure. Plan-File script also provides some built-in functions. These built-in functions operate on both primitive types and complex types. Because of Plan-File script is used to build software agents, it should support agent related operations. In particular, Plan-File script supports agent communications via FIPA ACL messages and operations on Directory Facilitator, including registration, search, modification and deregistration. It also supports launching other Plan-File based agents from Plan-File script and event handling. To make Plan-File script extensible, we design a mechanisms that enables Plan-File scripts to invoke functions written in different languages and described as Action-Files. Action-Files act as plug-ins to Plan-File scripts. Their invocation is handled by the interpreter. Examples of some useful Action-Files could be querying module to a database or a Web services invocation module. In order to give a flavour of our script language, an example of Plan-file for a contractor agent in the Contract Net Protocol [13] is presented in the Figure 3. <agent> <function name="say"> <in name="$words"/> <println>concat(getnickname(getaid()),' says:',$words)</println> </function> <event name="onterminate">  <say words="'deregistering services'"/> <df-deregister/> <say words="'service deregistered, terminating'"/> </event>  <assign var="$price" value="aslong(random(100,200))"/>  <df-register name="'contractor'" type="'fish'" protocol="'fipa-cnp'"/>  <receive msg="$m" performative="'cfp'" timeout="-1" protocol="'cnp'"/> <assign var="$manager" value="$m.sender"/>  <propose receiver="$manager" content="$price" protocol="'fipa-cnp'"/>  <receive msg="$m" sender="$manager" protocol="'fipa-cnp'" timeout="-1"/> <switch test="$m.performative"> <case value="'accept-proposal'">  <inform receiver="$manager" protocol="'fipa-cnp'"/> <break/> </case> <case value="'reject-proposal'"> <say words="'get rejected'"/> <break/> </case> </switch> </agent> Figure 3. Plan-File for a contractor in CNP

4 Conf. on Software Eng. Research and Practice SERP' Action-files Action-Files are building blocks of Plan-File scripts. Actually Action-Files provide advance functionality and extensibility to the system. A program described in the Action-File can be written in different languages. This means that if a user would like to use pre-programmed modules then their interface should be presented in Actionfile description and the interpreter take care about their invocation (at the moment Action-File written in Java are supported, however, we plan to provide interface to other languages as well). Figure 4 illustrates the relations between Plan-File scripts and Action-Files: 6 Interpreter Our goal is to make the architecture of the interpreter pluggable and to reduce the coupling among components. The whole Agora 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. The interpreter consists of the following components: Script-interpreting component: parse and execute the Plan-File script. Action-File manager: manages Action-Files as interpreter s libraries. FIPA handler: handles the FIPA operations by invoking the FIPA implementation component. Figure 4: Plan-File scripts and Action-Files GUI: a graphical user interface that enables users to run Plan-File script. Figure 5 illustrates the architecture of the interpreter. The Script-Interpreting component is the core of plan-file interpreter. The GUI component invokes the scriptinterpreting component to run a Plan-File script, while the printout of the Plan-File script is displayed in the GUI. The script-interpreting component parses and executes the Plan- File script and invokes the FIPA handler component if a FIPA operation is to be executed in the script. It also invokes the Action-File Manager component when an Action-File function invocation is executed in the script. As the entry point of the plan-file execution, the Script- Interpreting component also provides a Runner interface to the users.

5 300 Conf. on Software Eng. Research and Practice SERP'07 7 Scenario In order to demonstrate the features of Agora platforms and Plan-File scripts, we implement a specific shopping mall scenario. The shopping mall is represented by mall Agora. The mall Agora is a meeting place for customer agents and shop agents to trade products. As shown in Figure 6, the shopping mall Agora has a mall manager agent, several shop Agoras and customer agents. The mall manager agent is the default agent of the shopping mall Agora. The shop Agora represents specific Figure 5: Architecture of the interpreter shop in shopping mall. Each shop Agora has a shop manager agent, a negotiator agent and several shop agents. The shop manager agent and negotiator agent are default agents of the shop Agora. The shop manager agent is responsible for the registration and deregistration of customer agents, and it also performs matchmaking functions for customer agents. The negotiator agent is responsible for managing negotiation between customer agents and shop agents. The shop agents represent product sellers.

6 Conf. on Software Eng. Research and Practice SERP' Figure 6. Shopping mall Outside the shopping mall Agora, there is a bank Web Service. After the agreement is reached, the negotiator makes payment to the shop agent for customer agent via this Web service and the shop agent can check the payment using this service.. 8 Conclusions and future work A multi-agent system infrastructure may include different levels and components. We are mostly focused on cooperative work support component in the infrastructure. The platform we developed is based on the Agora concept as a facilitator of cooperative work and is implemented as a plug-in to the JADE system [15]. We see advantages of such approach we see as follows: it provides methodological and instrumental basis for cooperative work support in MAS it allows accumulation and re-use of knowledge about cooperative work by developing templates and libraries of typical solutions for cooperative work Our future work is oriented to development of more advanced and flexible GUI as well as extension of functionality of default components and maintenance of library of templates for typical agents and Agoras. 9 Acknowledgements This work was partially supported by the Norwegian Research Foundation in the framework of the VERDIKT program---the FABULA project. 10 References [1] J. M Bradshaw, S. Dutfield, P. Benoit, J. D. Woolley. KAoS: Toward an Industrial-Strength Open Agent Architecture. In: G. M. O Hare, N. R. Jennings, (eds.), Foundations of Distributed Artificial Intelligence, John Wiley & Sons, 1996, p [2] P. Cohen et al. An Open Agent Architecture, in Readings in Agent, M.N. Huhns and M.P. Singh, Editors. 1998, Morgan Kaufmann Publishers: San Mateo, CA. p [3] I. A. Ferguson. Touring Machines: An Architecture for Dynamic, Rational, Mobile Agents, in Clare Hall,. 1992, University of Cambridge: Cambridge, UK [4] K. Fischer, J. Meuller, and M. Pischel. A Pragmatic BDI Architecture, in Readings in Agent, M.N. Huhns and M.P. Singh, Editors. 1998, Morgan Kaufmann Publishers: San Mateo, CA. p

7 302 Conf. on Software Eng. Research and Practice SERP'07 [5] J. R. Graham and K. S. Decker. Towards a Distributed, Environment-Centered Agent Framework. In N. Jennings and Y. Lesperance (eds.), Intelligent Agents VI Proceedings of ATAL-99, Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, 2000 [6] B. Hayes-Roth. A Blackboard Architecture for Control. Artificial Intelligence, 26(3) (1985) [7] M. Matskin.. Multi-Agent Support for Modeling Cooperative Work. In: T. Yongchareon, F. A. Aagesen, V. Wuwongse (eds.) Intelligence in Networks. The Fifth International Conference SMARTNET'99, November 1999, Thailand, Kluwer Academic Publishers, (1999) [17] B. Henderson-Sellers, P. Giorgini (eds.). Agentoriented Methodologies. Idea group publishing, 2005 [18] R.H. Bordini, M. Dastani, J. Dix, El Fallah A. Seghrouchni. (Eds.). Languages, Platforms and Applications. Languages, Platforms and Applications. Series: Multiagent Systems, Artificial Societies, and Simulated Organizations, Vol. 15, Springer, 2005 [19] L. Padgham, M. Winikoff. Developing Intelligent Agent Systems (a practical guide), Wiley series in agent technology, 2004 [8] M. Matskin,, O. J. Kirkeluten, S. B. Krossnes and Ø. Sæle. Agora: An Infrastructure for Cooperative Work Support in Multi-Agent Systems. T. Wagner, O. Rana (eds.) Infrastructure for Agents, Multi-Agents, and Scalable Multi-Agent Systems. Springer Verlag, Lecture Notes in Computer Science, Volume 1887, 2001, pp [9] H. S. Nwana, Software Agents: An Overview. The Knowledge Engineering Review, (3). [10] H. S. Nwana, D. T. Ndumu, L C. Lee and J. C. Collos. ZEUS: A Tool-Kit for Building Distributed Multi-Agent Systems. Applied Artificial Intelligence Journal, Volume 13 (1), pp [11] G. M. Hare. Agent Factory: An Environment for the Fabrication of Multi-agent Systems. In: G. M. O Hare, N. R. Jennings, eds. Foundations of Distributed Artificial Intelligence. John Wiley & Sons, 1996, p [12] A.S. Rao, and M.P. Georgeff. BDI-agents: from theory to Practice. in ICMAS'95 - first International Conference on Multi-Agent Systems San Francisco, CA, USA, June 1995: AAAI Press. [13] R. G. Smith. The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver. IEEE Transactions of Computer Science, 29(12). (1980) [14] M. Wooldridge and N. Jennings. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, (2): p [15] F. L. Bellifemine, G. Caire, D. Greenwood. Developing Multi-Agent Systems with JADE. Wiley Series in Agent Technology, 2007 [16] P. R. Fillottrani., The multi-agent system architecture in SEWASIE. Journal of Computer Science and Technology, Vol. 5 No. 4, December 2005

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