Networked–Intelligent Software Agents & Agents NISA

1. Networked–Intelligent Software Agents & AgentsNISA Ahmed Hambaba Professor; Computer Engineering NISA June 7, 2002 Networked – Agents and Intelligent Software Agents Group (NISA)

2. NISA Mission MISSION The core of NISA Center is to develop intelligent software agent and agents technologies with focuses on integrated Business, Engineeringand Manufacturing. Its Vision is to serve as a center of excellence for the creation and dissemination of a systematic body of knowledge in information engineering systems and ultimately to impact next-generation products and service systems. The Center promotes research program, education, and community services to contribute to education and research infrastructure base. Networked – Agents and Intelligent Software Agents Group (NISA)

3. SOFTWARE AGENT TECHNOLOGIES Agent Communication Languages Support computing technologies Languages Traditional and Object – Oriented Languages Agent (scripting) languages Networked – Agents and Intelligent Software Agents Group (NISA)

4. INTELLIGENT SOFTWARE AGENT Learning & Adaptation Agent Communication Languages Support computing technologies Languages Traditional and Object – Oriented Languages Agent (scripting) languages Networked – Agents and Intelligent Software Agents Group (NISA)

5. NISA Platform & Tool Applications Agent communication Agent management Content languages Agent message transport Abstract Architecture Communicative Acts Interaction protocols Networked – Agents and Intelligent Software Agents Group (NISA)

6. NISA Objectives • Activity Areas • Industrial Research • Product & Solution Development • Consulting • Strategic Path • Horizontal: Platforms & Tools (NISA) • Vertical: • Communications & Networks • Diagnosis & Prognosis • Engineering, Manufacturing • Commerce, Finance Networked – Agents and Intelligent Software Agents Group (NISA)

7. NISA Application Types User Assistant Applications • These systems are those that work with, and in the interests of, an end- user in order to enhance their productivity and to ease the use of complex computer-based systems. • They are differentiated from standard user interfaces, in that they are empowered to act at least semi-autonomously, and are not merely tools that the user uses and controls. User profile learning systems Multimodal interface systems Personal Digital Assistant or Personal Intelligent Communicator applications(e.g., digital telephone secretary) Networked – Agents and Intelligent Software Agents Group (NISA)

8. NISA Application Types Information Retrieval Applications • These systems involve all the services needed to help the users in finding easily and quickly the information they request. This can be achieved for example by a society of agents. Directory services (yellow and white pages) Data Base enquiry Information Brokerage Media indexing Service Management Applications • These are systems that involve configuration and delivery of user requested services at the right time, cost, and QoS, while observing the required security and privacy issues. Multimedia services Buy/selling services(e.g., information, material goods) TMN/intelligent network management services Trip planning and guidance services(e.g., intermodal route planning, hotel and parking-lot reservations, individualised traffic guidance, tourism) Networked – Agents and Intelligent Software Agents Group (NISA)

9. NISA Application Types Business Management Applications • These systems deal with management of business tasks and resources in provision of services and carrying out business operations. Financial services Electronic commerce Workflow management Office automation Computer Supported Cooperative Work Telecommuting Networked – Agents and Intelligent Software Agents Group (NISA)

10. NISA Application Types Manufacturing Management Applications • These systems involve physically embodied agents designed to carry out and deal with management of tasks and processes in relatively structured industrial environments. These processes may involve the control of industrial robots and machines via software interfaces. Industrial Robotics Factory automation Virtual factory management Load Balancing Research Applications • These systems involve using agent technology to further research in other (IT) areas. Vision processing Learning and adaptive systems Speech processing Distributed knowledge-based systems Human-Computer Interface Networked – Agents and Intelligent Software Agents Group (NISA)

11. NISA Organization The Center shall conduct research, perform technology evaluation, provide the academic and industrial community with enhanced education capability in the field of Multi-Agent System Application in Engineering, Manufacturing and Software agent technology and facilitate information exchange and technology transfer. • The Center will be catalyzed by a small investment from SJSU and it is primarily supported by Center members, with NISA committees taking a supporting role in their development and evolution • Initially five-year program. • This five-year period allows for the development of a strong partnership between the academic researches and their industrial and government members. • The NISA center may enter into agreements with other universities to participate as additional. Networked – Agents and Intelligent Software Agents Group (NISA)

12. NISA Organization NSF Director IndustryAdvisoryBoard AcademicPolicyCommittee NISA Committee Collaborative Institutions Evaluator MISE Lab Manufacturing Information Systems Engineering Lab Client/Server Computing Lab Robotics Lab Human Computer Interface (HCI) Software Engineering Lab Networked – Agents and Intelligent Software Agents Group (NISA)

13. Organizational Structure The organizational structure of the Center comprises an Industrial Advisory Board (IAB), Center Site Director, and a University Policy Committee. The IAB, consisting of one voting member from each participating company, provides advice on research priorities and makes recommendations on projects to be funded. The Center Directory manages the day-to-day operation of the Center, acts as a liaison with member companies as well as the university administration and, in collaboration with the IAB, sets goals and future directions of research. The University Policy Committee, which consists of senior leaders the university, will assure that the Center’s activities are consistent with academic policies and procedures of the Universities. In addition, the Center has an external NSF evaluator to monitor and evaluate research interaction between Center researchers and company members. Networked – Agents and Intelligent Software Agents Group (NISA)

14. Objectives The objectives of the NISA Center are to: Conduct research to bring about innovation and practical solutions by focusing on industrially relevant research needs; Foster collaborative research projects between industrial and academic engineers and scientists; Promote interdisciplinary and inter-university research activities and to nurture students through testbeds and collaborative projects. Networked – Agents and Intelligent Software Agents Group (NISA)

15. Deliverables The center will deliver to its industry members the following: Development of software/hardware tools for manufacturing and engineering (e- diagnosis, e-prognosis, intelligent monitoring) using web-enabled and wireless technology; Implementation and demonstration of NISA architecture and its applications assets (machine manufacturing system, process, etc.); Test bed projects with collaborating member companies; Full-time and on-site post-docs and student resources for specific projects; and Interdisciplinary, well trained and system oriented engineers. Networked – Agents and Intelligent Software Agents Group (NISA)

16. NISA Center Requirements Develop a partnership among academe, industry and other organizations participating in the Center; Consult with Center members to set a defined research agenda focused on shared research interests, needs, and opportunities; Have Center members that monitor and advise on the progress of the research, which speeds two-way transfer of knowledge between universities and industry; Have a strong industry/university interaction program of university, industry, and other partners that are the primary financial resource for the Center; Rely on student involvement in high quality research projects, thus developing students who are knowledgeable in industrially relevant research; Membership agreement. Networked – Agents and Intelligent Software Agents Group (NISA)

17. NISA Center Requirements There must be a minimum of six Center members with a membership fee of $50,000 or higher per year. Other membership level categories with lower fees may be designated to encourage small company participation in the Center. An Industrial Advisory Board (IAB) that reviews ongoing and completed activities and recommends new projects. Networked – Agents and Intelligent Software Agents Group (NISA)

18. Industry Advisory Board (IAB) • Joe Pinto, Senior VP, Cisco • Marypat Farrell VP, Rockwell • Ben Bierman, Sr. Director, Applied Materials • Bob Togasaki, VP, HP • Glen Ahmann, Sr. Director, United Defense • Firth Griffith, Venture Capitalist Beachhead Capital • Mike Shafto, NASA Ames • BasheerJanjua, CEO, Integnology • Naoya Kinoshita, President MCC, Japan Networked – Agents and Intelligent Software Agents Group (NISA)

19. Industry • Cisco Systems • Applied Materials • United Defense • NASA Ames Research Center • MCC Corporation (Japan) • Integnology • Rockwell Automation Networked – Agents and Intelligent Software Agents Group (NISA)

20. Industry • Lockheed Martin Space Systems • Lam Research Lab • Solectron • Agilent • HP • Intel • KLA Tencor Networked – Agents and Intelligent Software Agents Group (NISA)

21. NISA Technical Committees • Ahmed Hambaba, Intelligent Software Agents • Kevin Corker, Human Computer Interface • M. E. Fayad, Object-Oriented Technology • Dan Harkey; C/S Computing • Hussein Salama, Content Delivery Networking • Rod Fatoohi, Computer Networks • Winncy Du, Robotic Systems • Moenes Iskarous, Intelligent Software Agents • Jacob Tsao, Manufacturing Systems Networked – Agents and Intelligent Software Agents Group (NISA)

22. University Collaboration NSF Industry/University Cooperative Research Center IMS Center University of Michigan IMS Center University of Wisconsin at Milwaukee NISA Center SJSU Networked – Agents and Intelligent Software Agents Group (NISA)

23. GOAL • NSF - Industry/University Cooperative Research Center on Networked-Intelligent Software Agents Networked – Agents and Intelligent Software Agents Group (NISA)

24. IMS CENTER @ SJSU NISA Group • Values to the IMS Center • Bring IT (ISA, Wireless, HMI) and intelligent agent focused technologies to IMS Center. • Adding Semiconductor Industry, Computer, and Networking Industries to IMS members • Foster alliance between the Silicon Valley Industry (Applied Materials, Cisco, United Defense, NASA) and IMS Industry Members Networked – Agents and Intelligent Software Agents Group (NISA)

25. NISA Architecture Overview Agents may have a need to obtain a service by other entities in the system. There are and in the future there will continue to be a wealth of non-agent software systems which provide useful services. Agents are to be truly useful they must be able to interface with and control existing software system such as databases, web- browsers, set-top boxes, speech synthesis programs and so forth. Software systems come in all shapes and sizes. Many different types of interfaces are possible each with their own particular networking protocol, strengths and weaknesses. Networked – Agents and Intelligent Software Agents Group (NISA)

26. NISA Architecture Overview There are a number of emerging distribution technologies such as CORBA, DCOM and Java-RMI which are creating (competing) standards for the integration of software systems and resources. Networked – Agents and Intelligent Software Agents Group (NISA)

27. Layered Model for a Wrapper Agent ACL Messages Wrapper Mapping to technology Java April ActiveX Java Orb Trader RMI TCP/IP DCOM RMI IIOP Web Server Legacy System Java Component Server CORBA Server SoftwareServices Networked – Agents and Intelligent Software Agents Group (NISA)

28. Reference Model of Agent based Adaptation Agent Platform A Agent Platform B Interface Agents Task Agents Information Agents Middle Agents Interface Agents Task Agents Information Agents Middle Agents Message Transport Agent Directory Service Directory ACL Message Transport Agent Directory Service Directory ACL IIOP IIOP WAP WAP TCP/IP TCP/IP Wireline WLAN WWAN Wireline WLAN WWAN Networked – Agents and Intelligent Software Agents Group (NISA)

29. General Agent Software Integration Scenario Broker query Client Agent Wrapper Software System invoke Networked – Agents and Intelligent Software Agents Group (NISA)

30. Characteristics of Agent Existing technologies Competitive XML technologies Autonomy independency persistency proxy/surrogate Distributed processing Persistent DB/daemon Fixed purpose proxy Intelligence Inference Interaction Dynamic interface adaptability rationality Distributed processing Persistent DB/daemon Fixed purpose proxy ebXML, WSDL XML Schema, SOAP, UDDI, e-speak Social ability Cooperation/ collaboration Competition Dynamic participation Distributed algorithm Cooperation protocol, workflow Auction, economic model Service advertisement ebXML, e-speak, WSDL CBL, CXML UDDI, e-speak, WSDL Mobility mobile agent Mobile object, process migration Networked – Agents and Intelligent Software Agents Group (NISA)

31. Applications Agent communication Agent management Content languages Agent message transport Abstract Architecture Communicative Acts Interaction protocols Networked – Agents and Intelligent Software Agents Group (NISA)

32. Why an Abstract Architecture? The first purpose of this work is to foster interoperability and reusability. Specifically, if two or more systems use different technologies to achieve some functional purpose, it is necessary to identify the common characteristics of the various approaches. This leads to the identification of architectural abstractions . By describing systems abstractly, one can explore the relationships between fundamental elements of these agent systems. From this set of architectural elements and relations one can derive a broad set of possible concrete architectures, which will interoperate because they share a common abstract design. Networked – Agents and Intelligent Software Agents Group (NISA)

33. MULTI-AGENT SYSTEM (MAS) User1 User 2 User u Goal and Task Specifications Results Interface Agent 1 Interface Agent 2 Interface Agent 3 Solutions Tasks Task Agent1 Task Agent2 Task Agent3 Information Integration Conflict Resolution Replies Info & Service Requests Middle agent 2 Information Agent 2 Information Agent 1 Advertisements Answers Queries DB1 DB2 DBm Networked – Agents and Intelligent Software Agents Group (NISA)

34. MULTI-AGENT SYSTEM (MAS) Abstract Architecture Interface Agents Task Agents Information Agents Middle Agents Message Transport Agent Directory Service Directory ACL Concrete realization: Java Concrete realization: CORBA Message Transport Agent Directory Service Directory ACL Message Transport Agent Directory Service Directory ACL Networked – Agents and Intelligent Software Agents Group (NISA)

35. MULTI-AGENT SYSTEM (MAS) Broker agent:An agent which provides the Agent Resource Broker (ARB) service. There must be at least one such an agent in each Agent Platform in order to allow the sharing of non-agent services. Agent:An Agent is the fundamental actor in a domain. It combines one or more service capabilities into a unified and integrated execution model which can include access to external software, human users and communication facilities. Agent Communication Language:A language with precisely defined syntax, semantics and pragmatics that is the basis of communication between independently designed and developed software agent. ACL is the primary subject of this part of the FIPA specification. Networked – Agents and Intelligent Software Agents Group (NISA)

36. MULTI-AGENT SYSTEM (MAS) Agent Communication Channel Router:The Agent Communication Channel is an agent which uses information provided by the Agent Management System to route messages between agents within the platform and to agents resident on other platforms. Agent Communication System:The Agent Management System is an agent which manages the creation, deletion, suspension, resumption, authentication and migration of agents on the agent platform and provides a “white pages” directory service for all agents resident on an agent platform. It stores the mapping between globally unique agent names and local transport addresses used by the platform. Networked – Agents and Intelligent Software Agents Group (NISA)

37. MULTI-AGENT SYSTEM (MAS) Agent Platform:An Agent Platform provides an infrastructure in which agents can be deployed. An agent must be registered on a platform in order to interact with other agents on that platform or indeed other platforms. An AP consists of three capability sets ACC, AMS and default Directory Facilitator. Software System:A software entity which is not conformant to the FIPA Agent Management specification. Networked – Agents and Intelligent Software Agents Group (NISA)

38. MULTI-AGENT SYSTEM (MAS) Interface agents–interact with users, receive user input, and display results. Task agents–help users perform tasks, formulate problem solving plans and carry out these plans by coordinating and exchanging information with other software agents. Information agents–provide intelligent access to a heterogeneous collection of information sources. Middle agents–help match agents that request services with agents that provide services. Networked – Agents and Intelligent Software Agents Group (NISA)

39. Background NISA’s goal in creating agent standards is to promote inter-operable agent applications and agent systems. At the heart NISA’s model for agent system is agent communication, where agents can pass semantically meaningful messages to one another in order to accomplish the tasks required by the application. How these messages are transferred (that is, the transport) How those messages are represented (e.g. s-expressions, bit- efficient binary objects, XML) Networked – Agents and Intelligent Software Agents Group (NISA)

40. Optional attributes of those messages, such as how to authenticate or encrypt them. It also became clear that to create agent systems, which could be deployed in commercial settings, it was important to understand and to use existing software environments. These environments included elements such as : Distributed computing platforms or programming languages Messaging platforms Security services Directory services, and, Intermittent connectivity technologies Networked – Agents and Intelligent Software Agents Group (NISA)

41. Because the abstract architecture permits the creation of multiple concrete realizations, it must provide mechanisms to permit them to interoperate. This includes providing transformations for both transport and encodings, as well as integrating these elements with the basuc elements of the environment. For example, one agent system may transmit ACL messages using the OMG IIOP protocol. A second may use IBM’s MQ-series enterprise messaging system. An analysis of these two – systems how senders and receivers are identified, and how messages are encoded and transferred – allows us to arrive at a series of architectural abstractions involving messages, encodings, and addresses. Networked – Agents and Intelligent Software Agents Group (NISA)

42. Going from Abstract to Concrete Specifications Such an architecture cannot be directly implemented, but instead the forms the basis for the development of concrete architectural specifications. Such specifications describe in precise detail how to construct an agent system, including the agents and the services that they rely upon, in terms of concrete software artefacts, such as programming languages, applications programming interfaces, network protocols, operating system services, and so forth. Several realizations have chosen to use this directory service model. Networked – Agents and Intelligent Software Agents Group (NISA)

43. Methodology This abstract architecture was created by the use of UML modeling, combined with the notations of design patterns. The analysis drew upon many sources: • The abstract notions of agency and the design features that flow from this. • Commercial software engineering principles, especially object-oriented techniques, design methodologies, development tools and distributed computing models. • Requirements drawn from a variety of applications domains. • Existing NISA specifications and implementations. • Agent systems and services, including NISA and non-NISA designs. • Commercial important software systems and services, such as Java, CORBA, DCOM, LDAP, X.500 and MQ Series. Networked – Agents and Intelligent Software Agents Group (NISA)

44. INTELLIGENT AGENTS Recently, research concerning the learning and adaptation of agents in multi-agent systems has gained considerable attention in both the Distributed Artificial Intelligence (DAI) and Machine Learning (ML) communicates. Agents must often learn in order to dynamically acquire the knowledge and skills necessary to improve their individual performance, precision, efficiency and scope of solvable problems during run-time. Networked – Agents and Intelligent Software Agents Group (NISA)

45. Neural Networks and Agent Learning In an agent-based system, agents learn through a variety of methods. • Rote learning: immediate and direct implantation of knowledge and skills without requiring further inferencing or transformation. • Isolated learning: concerned with having agents learn by themselves. Networked – Agents and Intelligent Software Agents Group (NISA)

46. Modeling Neural Network Knowledge Although a number of general specifications have been proposed for modeling the architecture of trained neural networks, these models lack a representation that provides meta-knowledge about a network. Neural Network Knowledge: The primary motivation for the use of a Neural Network Knowledge is to facilitate the probability of a wide variety of neural networks among heterogeneous agents and environments. Neural Network Knowledge may be represented in a number of languages including LISP, XML and KIF in order to facilitate their portability among a variety of environments. Networked – Agents and Intelligent Software Agents Group (NISA)

47. Communicating Neural Network Knowledge The identification of a protocol for communicating neural network knowledge between agents A protocol is required that allows a sending agent to express the context surrounding a communicated neural network knowledge to a receiving agent. Networked – Agents and Intelligent Software Agents Group (NISA)

48. Communicating Neural Network Knowledge Source Agent Target Agent Neural Network Knowledge Networked – Agents and Intelligent Software Agents Group (NISA)

49. Managing Neural Network Knowledge The specification of a multi-agent architecture for managing and using neural network knowledge. This specification defines a core set of services for creating, storing, managing and executing neural network knowledge. Networked – Agents and Intelligent Software Agents Group (NISA)

50. Placing This Work in Context The idea is that by using pre-existing knowledge, we may exploit knowledge reuse in neural networks that exist in different, but related domains and potentially save training time on new tasks. Such transfer has been shown to : • Accelerate learning of the target network • Reduce the number of required training examples of the target network • Improve the accuracy of the target network Networked – Agents and Intelligent Software Agents Group (NISA)