Principals, Practice & Experience JS01 June 4-6, 2001 XML + Semantics = DARPA Agent Markup Language (DAML) William Holmes, Dr. Paul Kogut Management & Data Systems Valley Forge, PA June 4, 2001

Principals, Practice & Experience Page 2 JS01 June 4-6, 2001 Roadmap l The Semantic Web l Agents & Ontologies l Object Management Group (OMG) Initiatives l The DARPA Agent Markup Language (DAML) u What is it? u How does it fit in? / What is its role? l LM M&DS UML-based Ontology Toolset (UBOT) u Ontology Design & Consistency Checking u Automated Annotation via AeroText TM

Principals, Practice & Experience Page 3 JS01 June 4-6, 2001 RING … RING... Hello? Hi Pete, its Lucy. Im at the doctors office. Mom needs to see a specialist and then has to have a series of physical therapy sessions. Biweekly or something. Can you split the chauffeuring with me? Sure Lucy. Semantic Web: The Vision Great! Ill have my agent set up the appointments. * Berners-Lee, Hendler, Lassila The Semantic Web Scientific American, May 2001

Principals, Practice & Experience Page 4 JS01 June 4-6, 2001 The Vision Semantic Web Lucys agent retrieves information about Moms prescribed treatment from the doctors agent. Lucys agent looks up several lists of providers and checks for ones in-plan for Moms insurance, within a 20-mile radius of her home, and with a rating of excellent or very good. Schedule a treatment plan for Mom using Pete and my schedules. Only use providers that are in-plan for Moms insurance, are within a 20-mile radius, and have a rating of excellent or very good. Lucys agent formulates a schedule of appointments for therapists with appointments available that fit into Pete and Lucys schedule. * Berners-Lee, Hendler, Lassila The Semantic Web Scientific American, May 2001

Principals, Practice & Experience Page 5 JS01 June 4-6, 2001 Thats Great but How? l Need Agents u Definition ( Merriam-Webster ): è one who is authorized to act for or in the place of another as a business representative u Provide a means of processing the volumes of information found on the web. l Need Ontologies u Definition: è Philosophy - A theory about the nature of existence. è A.I. - A formal definition of relations among terms. u Provide a semantic grounding for the web.

Principals, Practice & Experience Page 6 JS01 June 4-6, 2001 What are Agents? l In software, Agent is used in many different ways: è persistent process/daemon: è mobile code è autonomous robots è intelligent agent - what makes it intelligent? l simple definitions that capture the essence of agents: è an Object that decides when to say go and when to say no - OMG è programs that operate at a high enough semantic level that they can form new connections to other programs in order to get a job done Burstein, McDermott

Principals, Practice & Experience Page 7 JS01 June 4-6, 2001 Why Agents? l Agents are the next generation of middleware – built on top of existing middleware (e.g., CORBA, EJB, Jini) – run-time integration via dynamic discovery and resource negotiation – emphasis on broker and facilitator agents (e.g. yellow pages) l Agents are the next generation user interface – more complex applications require personal assistant agents – multi-modal interfaces e.g. speech, handwriting, gestures – user specifies goals and agent handles details according to user preferences Internet / Intranet agents personal assistant agent I need to go to Fort Worth on Monday for 3 days. itinerary, tickets & maps hotelscar rental airlinesmaps

Principals, Practice & Experience Page 8 JS01 June 4-6, 2001 Why Agents? (Cont.) l Agents are the next level of component abstraction u agents are components with attitudes è beliefs, desires, goals…* u agents interact like humans via speech acts è request, inform, promise u agents share a context for efficient communication è domain model ontologies are used at run-time è ontology agent/services - query, retrieve and translate ontologies *Labrou, Finin, Peng Agent Communication Languages:The Current Landscape IEEE Intelligent Systems March/April 1999

Principals, Practice & Experience Page 9 JS01 June 4-6, 2001 Examples of Agent Applications* u personal assistant - digital secretary – travel arrangements – meeting schedule coordination – personalized information filtering – mobile computing u internet/intranet information retrieval/summarization u electronic commerce u enterprise workflow - e.g., sales, order processing, shipping u military command and control u synthetic characters (e.g., Extempo Systems, Virtual Personalities) u robots - manufacturing, office, domestic u design and engineering *see Hendler Is There An Intelligent Agent in Your Future?

Principals, Practice & Experience Page 10 JS01 June 4-6, 2001 Ontologies l Machine readable semantic specifications. u Include terms, relations, and inference rules u What does capital mean? è Seat of government (Tallahassee, Harrisburg, Austin) è An upper-case letter è monies, securities, investments, etc… è the top of a column or pillar. l XML is Not Enough!!! u Allows definition of syntax, but not semantics (meaning) u Can be considered the Assembly Language of the Web.

Principals, Practice & Experience Page 11 JS01 June 4-6, 2001 OMG Initiatives l OMG Agent Platform Special Interest Group (SIG) u extend the OMG Object Management Architecture (OMA) to better support agent technology u identify and recommend new OMG specifications in the agent area u recommend agent-related extensions to existing and emerging OMG specifications u promote standard agent modeling techniques u see l OMG Ontology Working Group u Align the domain modeling activities of OMG with the Semantic Web initiative of the World Wide Web Consortium and with related ontology development projects such as DARPA DAML and IEEE SUO (Standard Upper Ontology).

Principals, Practice & Experience Page 12 JS01 June 4-6, 2001 DARPA Agent Markup Language l Machine-Readable Ontologies & Annotation (markup) l Aimed at Resources, Not just web-pages u Sensors u Services u Appliances l Lots of industry Buzz* u Scientific American u IEEE Distributed Systems u New York Times u ZDNet u … *See

Principals, Practice & Experience Page 13 JS01 June 4-6, 2001 DAML: Basic Idea web pages DAML annotation DAML ontologies agents web crawlers queries queries links annotate manually or semi-automatically DAML annotation RDBMS data schema queries queries links web pages, databases, legacy software, devices, sensors... have annotations linking their terms to ontologies

Principals, Practice & Experience Page 14 JS01 June 4-6, 2001 DAML Annotation: Extreme Metadata document parsing info Evolution of Metadata keywords XMLschema browser web crawler XMLparsers Subject verb object semantics for selected sentences Full semantics for all content agents(near-term)agents(future) implicit semantic agreements on paper! explicit semantic agreements via machine-readable ontologies

Principals, Practice & Experience Page 15 JS01 June 4-6, 2001 DAML Program l Main DAML website = l Duration: August 2000 to Fall 2002 l Approach: u MIT W3C semantic web activity è è The semantic Web and its languages in IEEE Intelligent Systems, November/December 2000, pages available at u Extend XML/RDF è represent ontologies è annotate web pages and other information with links to ontologies

Principals, Practice & Experience Page 16 JS01 June 4-6, 2001 DAML Program (Cont.) l 17 research teams and 1 integration team u industry, academia and World Wide Web Consortium u expertise in AI knowledge representation, logic and web technologies u cooperation with European Union IST Program è l DAML language definition u Ontology Definition u Rules Definition

Principals, Practice & Experience Page 17 JS01 June 4-6, 2001 DAML Program (Cont.) l DAML tools u ontology development and verification u web page annotation u dynamic composition of agent services u distributed query processing and inference u ontology translation l DAML trial applications u Government: Intelink, Center for Army Lessons Learned u Commercial: e-commerce, information retrieval

Principals, Practice & Experience Page 18 JS01 June 4-6, 2001 The Origins of DAML l Extensible Markup Language (XML) u provides syntactic interoperability u depends on implicit semantic agreements l Resource Description Framework (RDF) u designed to represent metadata for web resources in an XML syntax u triples: l RDF Schema (RDFS) u adds OO concepts: class and subclass XML RDF RDFS DAML * For more information see

Principals, Practice & Experience Page 19 JS01 June 4-6, 2001 Status of DAML l DAML+Oil (ontology) u released January latest revision March 2001 u language specifications and documentation: è u design rationale è l DAML-L (logic) u rule representation and reasoning u development in progress

Principals, Practice & Experience Page 20 JS01 June 4-6, 2001 UML-Based Ontology Toolset (UBOT) l We are applying: u graphical modeling and formal verification techniques from software engineering u text extraction from natural language processing u lexical semantic resources from cognitive science l to build a tool-set that supports u creation, extension and consistency checking of DAML ontologies u DAML annotation of information resources for agents l intended for users who have minimal training in knowledge representation and agent theory u see

Principals, Practice & Experience Page 21 JS01 June 4-6, 2001 UBOT Team l Lockheed Martin Management & Data Systems u architecture, development and integration l Versatile Information Systems (Northeastern University) u formal verification of UML l Lockheed Martin Advanced Technology Center u field test of DAML and UBOT l Kestrel Institute u automated formal methods

Principals, Practice & Experience Page 22 JS01 June 4-6, 2001 UBOT Architecture: Ontology Engineering DAML Ontology Engineer Extended DAML ontologies XMI models UML GUI UML Formalization Specware UBOT Slang models Consistency checking results Semantic inconsistencies UML DAML Translation XMI models Baseline DAML ontologies

Principals, Practice & Experience Page 23 JS01 June 4-6, 2001 UBOT Architecture: Annotation DAML Annotator DAML annotated text or web pages UML GUI Text Extraction Text or web pages UML DAML Translation Extraction to DAML Translation XMI DAML Ontologies automatically generated uncorrected annotation corrected annotation UBOT

Principals, Practice & Experience Page 24 JS01 June 4-6, 2001 UBOT Architecture: COTS Components l UML GUI u Tau UML Suite (Telelogic) l Specware (Kestrel Institute) u supports ontology consistency checking via formal methods u SNARK theorem prover (SRI) l Text Extraction u AeroText (LM M&DS) è extracts entities (e.g. people, organizations, etc.) from natural language è recognizes relationships between entities (e.g. [organization] hired [person] ) è developed for the U.S. Intelligence Community è 12 years experience with sophisticated linguistic processing è many fielded applications

Principals, Practice & Experience Page 25 JS01 June 4-6, 2001 UML GUI: Tau UML Suite

Principals, Practice & Experience Page 26 JS01 June 4-6, 2001 Text Extraction: AeroText Document Window Extraction Display

Principals, Practice & Experience Page 27 JS01 June 4-6, 2001 Automatic Annotation: AeroDAML

Principals, Practice & Experience Page 28 JS01 June 4-6, 2001 Questions?