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DARPA Agent Markup Language November 2001

DARPA Agent Markup Language November 2001. Enabling “agent” communication at a Web-wide scale. Murray Burke Information Exploitation Office. Military Systems are Moving to the Web. Joint Battlespace Infosphere Theater Battle Management Core System BroadSword Air Mobility Command GDSS.

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DARPA Agent Markup Language November 2001

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  1. DARPA Agent Markup LanguageNovember 2001 Enabling “agent” communication at a Web-wide scale. Murray Burke Information Exploitation Office

  2. Military Systems are Moving to the Web • Joint Battlespace Infosphere • Theater Battle Management Core System • BroadSword • Air Mobility Command GDSS • Center for Army Lessons Learned • Warrior Knowledge Network • Web Mapping Testbed Army JointGlobal Command & Control System • Global Command Support System • JOPES 2000 • Advanced Course Of Action ACTD • CINC21 • Joint Center for Lessons Learned Air Force • Expeditionary Sensor Grid • Task Force Web • Navy Lessons Learned System • Navy Warfare On-Line Library • Air – Ground Combat System • Distance Learning Network • Logistics Bases Inventory Visibility • Items Applications On-Line • Master Header Information On-Line Intelligence Community • Intelink • Joint Intelligence Virtual Architecture • Horus • Crypto Analysis Web • NIMA Geospatial Engine Navy Marines

  3. Web Limitations Doubles in size every six months Average WWW searches examine only about 25% of potentially relevant sites Problems grow worse as Web continues to grow World Wide Web Intelink-S Intelink Information on web is not suitable for software agents Web searches return a lot of unwanted information

  4. DAML The Evolution of the Web World Wide Web HTML • Formatted for humans to read via web browsers • Formatted for machine readability but with very limited semantics XML Semantic Web Machine readability with very rich semantics to support agents for: • Intelligence Analysis and Production • Military Planning and Operations • Software C4ISR Agents • Sensor Fusion DAML is building the language and tools to realize the bold vision of the Semantic Web

  5. Web Migration to New Technology “In 30 years e-commerce will have become second nature. Lifelike, intelligent virtual assistants will be performing most routine transactions and simple negotiationselectronically on our behalf. More technological change will have taken place in that period than during the entire twentieth century, and the curve will continue to steepen exponentially into the foreseeable future.” Ray Kurzweil 100% HTML DAML 50% XML “Fifty percent of the content on the Web will be in XML format by the end of 2003” ……….Gartner Group 0% 2010 2000 2005

  6. Determine Force Mix Get Weather Info ProvideIntelligence Update Coordinate Transportation Order Supplies Select Targets The Bold Vision – DistributedAgents on the Semantic Web “Make preparations to capture Bagram air base.”

  7. Query Today WWW Hotbot What is Al Qaeda? The answer may be somewhere in this list of URLs

  8. Semantic Query What is Al Qaeda? A terrorist organization Would you like additional information on? • Membership • Locations • Structure • Finances • Tactics • Other terrorist organizations

  9. What’s Hard? Scale Scope and Lack of Consistency in Global C2I Networks • Diversity: Ontologies and Ontology Mapping • Markup Simplicity: • Automatically Derived Markup • Constrained Logic • Enabling Software Agents to Locate and Use Appropriate Services: • Services description language • Infrastructure: Yellow Pages, Brokers, Mediaters • Trust: Logical Proofs

  10. Precedents 1995 . . . . . . . . . . . . . . . . . . . . .1998 2000 . . . . . . . . . . . . . . . . . . . . 2003 Dozens of knowledge representation languages Dozens of application design languages Odell Booch Rumbaugh KREME Loom RDF Rational Rose Paradigm Plus KEE KIF OMG DARPA / W3C DAML UML One modeling language One Web KR language

  11. DAML Foundation Language to describe information Tools for users and developers Transition activities DAML • Semantic Web • WWW • NIPRNET • INTELINK-S • INTELINK

  12. Developing the Language • Formal Logics • Knowledge Representation • Reasoning AI Community European OIL Community Local Environments DARPA DAML DAML + OIL US – EU DAML Joint Committee WWWEnvironment • HTML • XML • RDF W3C Web Standards WebOnt WG

  13. Example Ontology These ontologies accessed at remote locations

  14. DAML Example (Markup) <?xml version='1.0' encoding='ISO-8859-1'?> <!DOCTYPE rdf:RDF [ <!ENTITY rdf 'http://www.w3.org/1999/02/22-rdf-syntax-ns#'> <!ENTITY countries-ont 'http://www.daml.org/2001/09/countries/iso-3166-ont#'> <!ENTITY cities-ont 'http://www.daml.ri.cmu.edu/ont/City.daml#'>] <rdf:RDF xmlns:rdf ="&rdf;" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:daml="http://www.daml.org/2001/03/daml+oil#" <daml:Ontology rdf:about=""> <daml:versionInfo>$Id: map-ont.daml,v 1.2 2001/06/16 13:44:29 mdean Exp $</daml:versionInfo> <rdfs:comment>Map Overlay Ontology</rdfs:comment> </daml:Ontology> <rdfs:Class rdf:ID="TerroristEvent"> <rdfs:subClassOf> <daml:Restriction> <daml:onProperty rdf:resource="#name"/> <daml:toClass rdf:resource="http://www.w3.org/2000/10/XMLSchema#string"/> <daml:maxCardinality>1</daml:maxCardinality> </daml:Restriction> </rdfs:subClassOf> <rdfs:subClassOf> <daml:Restriction> <daml:onProperty rdf:resource="#location"/> <daml:toClass rdf:resource="#Location"/> <daml:maxCardinality>1</daml:maxCardinality> </daml:Restriction> </rdfs:subClassOf> <rdfs:subClassOf> <daml:Restriction> <daml:onProperty rdf:resource="#date"/> <daml:toClass rdf:resource="http://www.w3.org/2000/10/XMLSchema#date"/> <daml:maxCardinality>1</daml:maxCardinality> </daml:Restriction> </rdfs:subClassOf> </rdfs:Class> rdfs:Class rdf:ID="Terrorist"><rdfs:subClassOf> <daml:Restriction><daml:onProperty rdf:resource="#name"/><daml:toClass rdf:resource="http://www.w3.org/2000/10/XMLSchema#string"/></daml:Restriction></rdfs:subClassOf><rdfs:subClassOf> <daml:Restriction><daml:onProperty rdf:resource="#citizenOf"/> <daml:toClass rdf:resource="&countries-ont;Country"/> </daml:Restriction></rdfs:subClassOf><rdfs:subClassOf><daml:Restriction><daml:onProperty rdf:resource="#residesIn"/><daml:toClass rdf:resource="&countries-ont;Country"/> </daml:Restriction></rdfs:subClassOf></rdfs:Class>

  15. Agent-Based Inferencing • If x is Bin Laden, he must be a terrorist • If x is a terrorist, then he may or may not be Bin Laden • If x is not a terrorist, then he is not Bin Laden • If x is not Bin Laden, he may or may not be a terrorist <daml:Class rdf:ID=“Bin Laden"> <rdfs:subClassOf rdf:resource="#terrorist"/> </daml:Class> Implies

  16. DAML Services Ontology Service Resources provides presents supports Service Profile Service Grounding describedBy How to access it What the service does Service Model How it works

  17. Determine Force Mix Get Weather Info Provide Intelligence Update Coordinate Transportation Order Supplies Select Targets Developing the Tools Operational Prototype Tools APIs Report Generator Browser Edit Validation/Analysis Inference Visualize/ View Parser Search/Query Import Transform Developer and User Tools Semantic Web

  18. Language & Tools Transition DAML Language Specification W3C WebOnt Standard Feedback Loop Commercial Tools DAML Prototype Tools Feedback Loop Near-term C2I Applications Longer-term Military & Commercial Applications

  19. DAML Language Strategy Ontology Logic W3C Standardization Proof • Formal Semantic Underpinnings • Model-Based • Axiom-Based Trust

  20. Transition Process • Focal Point for Military Early Adopters • 60 Attendees at First Conference • 100 Expected at 2nd Conference on 13-14 Nov DAML DoD Projects • Intelink Management Office: Horus • Navy: Expeditionary Sensor Grid • Air Force: Foreign Clearance Guide • Army: Center for Lessons Learned • Army: Warrior Knowledge Network • TRANSCOM: Global Transportation Network • Air Force: Joint Battlespace Infosphere • Navy: Task Force Web (Identify Requirements) DAML Semantic Web for Military Users Conferences

  21. Horus IMO paid half in FY 00, FY 01 and FY02 ~ $1.5M each year

  22. Intelink Transition • Intelink has 150K users and expects 400K users by end of 2002 • A controlled testbed, effectively a microcosm of the WWW • A quick military transition of emerging DAML technologies • Quotes from Intelink Management Office (IMO) Conference • “Terrific New Alliance With DARPA” • “IMO Has Linked to DARPA’s DAML Program • Tim Berners-Lee, Ralph Swick etc (The “A” team)” • “Large Opportunity For Web Technologies • Many Models On Internet • Many We Can Develop With DARPA”

  23. Getting the Word Out DAML LAB @ DARPA TIC 18 DAML Research Teams www.daml.org www.daml.net PKI • Mail Lists • Web Server • Software Repository • Ontology Library • HotDAML Newsletters • Scientific American Article Internet Lots of Interest From the Rest of the World (Almost Two Million Hits)

  24. DAML in 2002 DAML Tools Releases in May and September DAML Integrated Demonstration & Experiment Horus ESG DAML Language Other DAML Research Team Metrics Feedback

  25. Weather Web Site Weather Ontology Weather Web Site Weather Web Site DAML DEMONSTRATION AND EXPERIMENT CONCEPT OF OPERATIONS Air Force Lessons Learned System Joint Battlespace Infosphere (JBI) Semantic Web Planner DAML Foreign Clearance Guide Markup Navy Expeditionary Sensor Grid DAML Rapid Knowledge Formation (translation) DAML DAML DAML Air Force Plan Markup Air Force Lessons Learned Markup Internet for demo But could be SIPRNET for real application Unifying Ontology (GEOLOC) DAML CIA Fact Book Markup .NET .ASP Server & DAML Query & Inference Engine Legacy Data Bases DAML AT2000 Military or DoD User Agents Ontology Editing Tool(s) Web Browser Creates / Accesses DAML ontologies & content Transition Programs Provides support to military user via his/her Web Browser Acts as proxies for senior military users to do background tasks Complex querying and inferencing about plan information Actual DAML ontologies & content

  26. Now 1 Node 1 Ontology 3 Data Base 0 Agents 6 Months 3-4 Nodes 4 Ontologies 3-5 Data Bases 1 Agents 12 Months 4-5 Nodes 6-8 Ontologies 5-7 Data Bases 3-5 Agents Metrics Millions of Nodes Millions of Ontologies Millions of DBs Millions of Agents Millions of Nodes Millions of Ontologies Millions of DBs Millions of Agents 2002 Experiment Millions of Nodes Millions of Ontologies Millions of DBs Millions of Agents Vision • Millions of Nodes • Millions of Ontologies • Millions of Data Bases • Millions of Agents • Active on the Semanic Web

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