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Agent technology Enabling communication among tools and data

Agent technology Enabling communication among tools and data. Thomas E. Potok Collaborative Technologies Group Leader Computer Science and Mathematics Division Oak Ridge National Laboratory. Mladen Vouk Professor of Computer Science

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Agent technology Enabling communication among tools and data

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  1. Agent technology Enabling communication among tools and data Thomas E. Potok Collaborative Technologies Group Leader Computer Science and Mathematics Division Oak Ridge National Laboratory Mladen Vouk Professor of Computer Science Technical Director of the NC State Center for Advanced Computing and Communications North Carolina State University

  2. AGENTS Internet Telephone Face to Face Agent Technology Trend Tim Berners-Lee – “The Semantic Web… will open up the knowledge and workings of humankind to meaningful analysis by software agents, providing a new class of tools by which we can live, work and learn together” “The Semantic Web” Scientific American 5/2001

  3. Successful Projects VIPAR Knowledge Discovery • We have extensive expertise in agent development • Began working with agent technologies in 1980s Supply Chain Management Agent System Manufacturing Emulation Agent System Collaborative Decision Support System Neural Nets for Recovery Boiler Control Neural Nets for Bankruptcy Prediction Neural Nets for Spring-back Prediction Collaborative Design System Neural Nets for Resistance. Spot Welding Neural Nets for Material Mix Optimization Genetic Algorithms for Chemical Synthesis • Over 10 successful projects within the last 5 years • Collaborations with leading agent experts Knowledge-based Systems - Manufacturing Advisors Knowledge-based Systems for Constructability Design and Analysis of Computer Experiments Knowledge-based Computer Systems Calibration 1985 1990 1995 2000

  4. What are Agents? ...Software entities that assist people and act on their behalf - IBM ...Software “robots” Proactive detect changes in their environment and react to those in a timely manner by answering to events and initiating actions Traditional Software Object Goal-driven have a purpose and act in accordance with that purpose until it is fulfilled Behavior State Agent Technology Communicative able to interact and communicate with users and other agents Autonomous can have control over their own actions and be able to work and launch actions independent of the user or other actors Learning have the ability to learn from experiences in their environment

  5. Typical Agent Architecture MULTIAGENT APPLICATION (Agent-User Interface, Conversation Interface) SOCIAL MODEL (Interaction rules, Conversation Management) Legacy Databases INFERENCE ENGINE (Decision Support Models) LOCAL MODEL (Domain KB, Ontologies) Legacy Software LINGUISTIC LAYER (Message Syntax and Semantics) COMMUNICATION PROTOCOL LAYER (Multicast, Directed Communication) LEARNING LAYER INFRASTRUCTURE (e.g., Java Virtual Machine) OPERATING SYSTEM HARDWARE

  6. Current Agent Funding • NSF: • Division of Information and Intelligent Systems • Division of Electrical and Communications Systems • Computation and Social Systems • Knowledge and Cognitive Systems • Control, Networks, and Computational Intelligence (CNCI) • DARPA: • Information Technology Office • Control of Agent-Based Systems (CoABS) • DARPA Agent Mark Up Language (DAML) • Taskable Agent Software Kit (TASK) • Office of Naval Research: • Information, Electronics & Surveillance • Intelligent Systems • Others include: • NASA, Army, Air force, Office of the Secretary of Defense, NIST, …

  7. Simple Agent Example Agent, find me the book “War and Peace,” and I need it tomorrow Dedicated Agents Amazon 2 Days $18.50 Barnes and Nobel 1 Day $21.75 B. Dalton 1 Day $20.25 Agent Communities Library 1 Day Free Does the agent understand buying books? Form a plan to buy the book eBay 1 Day $12.50 Execute the plan

  8. VIPAR Project – US Pacific Command • Analysts Search 20-30 papers a day • Manually find the articles on internet • Manually organizing the articles Unorganized Newspaper Articles Analysts Organized Results Inside China NEA Russia Today SEA Jakarta Post Oceania

  9. New Intelligent Agent Approach Intelligent Agent Inside China Analysts Economy Russia Today Military Jakarta Post Political Retrieval Agents Vector Perturbation Clustering “Knowledge Bins”

  10. Oak Ridge Mobile Agent Community (ORMAC) Communication Machine A Machine B Agent Host X Agent Host Y Agent Host Z Agent Context Agent Context Agent Context Agent 1 Agent 2 Agent 3 • Allows agents to be transmitted and received among machines. • Agents can also interact with systems and agents that are not part of the community. • Agents uses the Foundation for Intelligent Physical Agent (FIPA) compliant agent control language (ACL) messages.

  11. Whiteboard Agent GTP Agent Information Agents Information Agents Information Agents Information Agents Cluster Agent … Information Agents External Agents … External Agents VIPAR Architecture RDF Ontologies Conversion from HTML to XML Dynamic Vector Space Models Multi-agent System Built on ORMAC Framework

  12. D1 D2 D3 Clustering: A Simple Example 1. Original and Parsed Documents 2. Terms Dictionary 3. Vector Space Model 4. Document Similarity 5. Euclidean Distance 7. Phylips tree representation 6. Agglomerative Hierarchical Clustering Agglomerative Divisive 8 1 2 3 4 6 7

  13. VIPAR Knowledge Management Same result, easier to “see” 3 2 • Wen Ho Lee • Wen Ho Lee Spends First Day Savoring Home Delights • Clinton Calls For Review Of Lee Secrets Case • Clinton Concerned Over Lee Case - Reno On Defensive • Asian-Americans Demand White House Action on Lee • Lee Case Points up Scientists' Attitude on Security • India and Pakistan • India and Pakistan: Troubled relations • Troops die in Kashmir clashes • IAEA Meeting • IAEA Supports Putin Nuclear Power Initiative • China Rejects Moves to Tighten Regulation of Nuclear Materials • U.S. China Trade • U.S. China Trade Vote Milestone on Rocky Road 4 1 Wen Ho Lee 5 US China Trade India/Pakistan 6 IAEA Meeting 10 7 9 8

  14. Endorsements • US Pacific Command’s CINC Admiral Blair • “A tremendously successful project” • “Software agents … lead to substantially improved analytical products.” • US Pacific Command’s Science and Technology Advisor • “hit a grand slam home run!” • “first time we've seen information discovery and knowledge management software working here at HQ USCINCPAC operationally.”

  15. How agents can work for scientific data

  16. Astrophysics simulation of temperature and tangential velocities Visualization created by Ross Toedte

  17. Hypothetical Scenario Probe Data Reduction Agent Clustering Agent Parallel IO Agent Astrophysics Simulation Stripe Analysis Binning Sampling Dynamic Clustering Astrophysics Data Agent MPI-IO HPSS Storage Agent Full Data Reduced Data Clustered Data

  18. Example SDM Agent Community Scientist: What if we reduce the data? A5 A1 A2 A3 A4 Agent whiteboard A1: REQUEST All: Dimensionality Reduction FORMAT: HDF5 XML TYPE: Climate A2: REPLY A1: Dimensionality Reduction FORMAT: HDF5 TYPE: General A3: REPLY A1: Dimensionality Reduction FORMAT: ASCII TYPE: Physics A1: REQUEST All: Conversion FORMAT: HDF5 XML to HDF5 TYPE: any A4: REPLY A1: Conversion FORMAT: HDF5 XML to HDF5 TYPE: Nuclear A5: REPLY A1: Conversion FORMAT: HDF5 XML to HDF4 XML TYPE: any A1: PERFORM A4: Conversion FORMAT: HDF5 XML to HDF5 DATA: D1 A4: RESULT A1: Conversion FORMAT: HDF5 XML to HDF5 Data: R1 A1: PERFORM A2: Dimensionality Reduction FORMAT: HDF5 Data: R1 A2: RESULTS A1: Dimensionality Reduction FORMAT: HDF5 Data: R2

  19. Year 1 Deliverables • Generic scientific data ontology • Current framework supports a standard FIPA message ACL • Need for agents to be able understand and interact with scientific data • Data centric? • Tool centric? • Analysis centric?

  20. Year 1 Deliverables continued • Generic data and model agents for data mining and discovery of access patterns • Define general case agents that can be adapted to work with • Specific data types • Specific tools • Establish network-based software configuration, management and distribution site

  21. Summary • Intelligent agents are a significant future technology direction • We have a significant progression of deployed agent systems and research to our credit • We have ringing endorsements regarding the success of our systems and research • We look forward to the next steps…

  22. How to use agents? • We do not what to redo what you have already done!!! • We want to supply the data communication protocols so that scientists can use your tools more effectively • Java based, FIPA compliant

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