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1 Intelligent Information Systems on the Web and in the Aether Tim Finin University of Maryland Baltimore County March 21, 2003

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Presentation on theme: "1 Intelligent Information Systems on the Web and in the Aether Tim Finin University of Maryland Baltimore County March 21, 2003"— Presentation transcript:

1 1 Intelligent Information Systems on the Web and in the Aether Tim Finin University of Maryland Baltimore County March 21, Joint work with Scott Cost, Benjamin Grosof (MIT), Anupam Joshi, Jim Mayfield (JHU), Charles Nicholas, Yun Peng, Yelena Yesha & many students. This work was partially supported by DARPA contract F , NSF grants CCR and IIS and grants from IBM, Fujitsu and HP. tell register tell register

2 UMBC an Honors University in Maryland 2 (1) Opening thoughts (2) Some current SW related research at UMBC (4) Parting thoughts

3 UMBC an Honors University in Maryland 3 XML is Lisp's bastard nephew, with uglier syntax and no semantics. Yet XML is poised to enable the creation of a Web of data that dwarfs anything since the Library at Alexandria. -- Philip Wadler, Et tu XML? The fall of the relational empire, VLDB, Rome, September 2001.

4 UMBC an Honors University in Maryland 4 The web has made people smarter. We need to understand how to use it to make machines smarter, too. -- Michael I. Jordan, paraphrased from a talk at AAAI, July 2002 by Michael Jordan (UC Berkeley)

5 UMBC an Honors University in Maryland 5 The Semantic Web will globalize KR, just as the WWW globalize hypertextThe Semantic Web will globalize KR, just as the WWW globalize hypertext -- Tim Berners-Lee

6 UMBC an Honors University in Maryland 6 The multi-agent systems paradigm and the web both emerged around One has succeeded beyond imagination and the other has not yet made it out of the lab. -- Anonymous, 2001

7 UMBC an Honors University in Maryland 7 IMHO The web is like a universal acid, eating through and consuming everything it touches. The web is like a universal acid, eating through and consuming everything it touches. Web principles and technologies are equally good for wireless/pervasive computing. Web principles and technologies are equally good for wireless/pervasive computing. The semantic web is our first serious attempt to provide semantics for XML sublanguages. The semantic web is our first serious attempt to provide semantics for XML sublanguages. The semantic web will provide mechanisms for people and machines (agents, programs, CGI scripts) to come together. The semantic web will provide mechanisms for people and machines (agents, programs, CGI scripts) to come together. Again: in all kinds of networked environments: wired, wireless, ad hoc, wearable, etc. Again: in all kinds of networked environments: wired, wireless, ad hoc, wearable, etc. Solving the symbol grounding problem? Solving the symbol grounding problem?

8 UMBC an Honors University in Maryland 8 Some UMBC applications (1) Semantic web and agents (ITTalks) (2) Ontology mapping (3) Cooperating personal agents (4) Learning markup (5) Information retrieval on the SW (6) Modeling trust policies (7) SW meets pervasive computing (8) SW and trading agents

9 UMBC an Honors University in Maryland 9 (1) ITTALKS (1) ITTALKS ITTALKS is a database driven web site of IT related talks at UMBC and other institutions. The database contains information on ITTALKS is a database driven web site of IT related talks at UMBC and other institutions. The database contains information on – Seminar events – People (speakers, hosts, users, …) – Places (rooms, institutions, …) Web pages with DAML markup are generated Web pages with DAML markup are generated The DAML markup supports agent-based services relating to these talks. The DAML markup supports agent-based services relating to these talks. Users get talk announcements based on the interests, locations and schedules. Users get talk announcements based on the interests, locations and schedules.

10 UMBC an Honors University in Maryland 10

11 UMBC an Honors University in Maryland 11 human view

12 UMBC an Honors University in Maryland 12 machine view

13 UMBC an Honors University in Maryland 13 ITTALKS Architecture Web server + Java servlets DAML reasoning engine DAML files Agents Databases People RDBMS DB , HTML, SMS, WAP FIPA ACL, KQML, DAML SQL HTTP, KQML, DAML, Prolog MapBlast, CiteSeer, Google, … HTTP HTTP, WebScraping Web Services Apache Tomcat

14 UMBC an Honors University in Maryland 14 ITTALKS Ontologies Weve defined and use the following ontologies, all at Weve defined and use the following ontologies, all at calendar-ont.daml – calendar and schedule info calendar-ont.daml – calendar and schedule info calendar-ont.daml classification.daml – ACM CCS topics classification.daml – ACM CCS topics classification.daml person-ont.daml – people and their attributes person-ont.daml – people and their attributes person-ont.daml place-ont.daml – talk locations place-ont.daml – talk locations place-ont.daml profile-ont.daml – user modeling info profile-ont.daml – user modeling info profile-ont.daml talk-ont.daml – talks info talk-ont.daml – talks info talk-ont.daml topic-ont.daml – topics and interests topic-ont.daml – topics and interests topic-ont.daml

15 UMBC an Honors University in Maryland 15 How does DAML Help? ontology language user models interop language agent communication service description language DAML+OIL provided a uniform language which met Many needs in developing a complex application.

16 UMBC an Honors University in Maryland 16 Two Advanced Capabilities Ill briefly describe two advanced capabilities facilitated by DAML: Ill briefly describe two advanced capabilities facilitated by DAML: Classifying talk topics and user interests using DAML ontologies Classifying talk topics and user interests using DAML ontologies Using DAML as a communication language among software agents Using DAML as a communication language among software agents

17 UMBC an Honors University in Maryland 17 (2) Ontology mapping Techniques for mapping between ontologies are thought to be important for the semantic web. Techniques for mapping between ontologies are thought to be important for the semantic web. Ontology mapping is a complex problem Ontology mapping is a complex problem Even in our simple ITTALKS system weve found a need to map between limited ontologies. Even in our simple ITTALKS system weve found a need to map between limited ontologies.

18 UMBC an Honors University in Maryland 18 What are talks about? Topic hierarchies provide indexing terms Topic hierarchies provide indexing terms ACM CCS topic hierarchy ACM CCS topic hierarchy ACM CCS ACM CCS Open Directory Open Directory Open Directory Open Directory Encoded as DAML ontologies Encoded as DAML ontologies These allow users to specify interests as well as browse the database of talks by topic These allow users to specify interests as well as browse the database of talks by topic Automatic classification of talks (based on title and abstract) and users (based on his web pages, CV, papers, etc.) Automatic classification of talks (based on title and abstract) and users (based on his web pages, CV, papers, etc.) Discovery of mapping rules between CCS to OD ontologies using IR techniques Discovery of mapping rules between CCS to OD ontologies using IR techniques

19 UMBC an Honors University in Maryland 19 Classifying Talks ACM CCS Ontology Training corpus CMU Bow statistical Bow text analysis tools CMU Bow statistical Bow text analysis tools ACM CCS classifier Now is the time for all good men to come to the aid of the country. Now is the time for topics e.g.: ACM CCS e.g.:5K ACM abstracts Topics Ontology uses

20 UMBC an Honors University in Maryland 20 Mapping between topic ontologies Topic ontology T1 Training corpus T1 CMU Bow statistical Bow text analysis tools CMU Bow statistical Bow text analysis tools T1 T2 mapper {(t2:bar, 0.8), (t2:qux, 0.7), …} Topic ontology T2 Training corpus T2 T1 T2 t1:foo

21 UMBC an Honors University in Maryland 21 Interactive topic ontology mapper Users create maps between ontologies with URIs to text describing classes & properties. Users create maps between ontologies with URIs to text describing classes & properties. Automates mapping process, taking into account hierarchical relationships and user-specified landmark mappings. Automates mapping process, taking into account hierarchical relationships and user-specified landmark mappings. Text classification used to compute similarities between topics. Text classification used to compute similarities between topics. A probabilistic approach used to combine hierarchical information. A probabilistic approach used to combine hierarchical information. Used in XTalks to enable mappings between Alternative topic ontologies in DAML+OIL

22 UMBC an Honors University in Maryland 22 General Ontology mapping Ontology mapping is a complex problem, and external information is needed to simplify it. Ontology mapping is a complex problem, and external information is needed to simplify it. We are working to extend this approach as a technique for semi-automatic generation of maps from one DAML+OIL ontology to another. We are working to extend this approach as a technique for semi-automatic generation of maps from one DAML+OIL ontology to another. External information, e.g., text associated with properties and classes, suggests nodes to equate. External information, e.g., text associated with properties and classes, suggests nodes to equate. Structural information produces contradictions or assumptions which must be made if the nodes are equated. Structural information produces contradictions or assumptions which must be made if the nodes are equated.

23 UMBC an Honors University in Maryland 23 (3) DAML and Agents Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure such as the DARPA Grid Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure such as the DARPA GridKQMLFIPADARPA GridKQMLFIPADARPA Grid The paradigm has been peer-to-peer message oriented communication mediated by brokers and facilitators. The paradigm has been peer-to-peer message oriented communication mediated by brokers and facilitators. The DAML program invites different paradigms which will require some changes in ACLs and their associates software systems. The DAML program invites different paradigms which will require some changes in ACLs and their associates software systems. Agents publish beliefs, requests, and other speech acts on web pages. Agents publish beliefs, requests, and other speech acts on web pages. Agents discover what peers have published on the web. Agents discover what peers have published on the web. The software agent research community is very interested in the semantic web and DAML The software agent research community is very interested in the semantic web and DAML

24 UMBC an Honors University in Maryland 24 MS Outlook XSB DAML+OIL Reasoner ITTALKS agent Travel agent Calendar agent User agent Broker Agent Agent Name Server users daml profile mapquest MS Outlook ITTALKS app Common agent infrastructure FIPA ACL API Communication protocol

25 UMBC an Honors University in Maryland 25 XTalks Personal Agent XPA is a configurable personal agent which accepts FIPA messages from XTalks and other instances of XPAs as well as applications, e.g. MS Outlook. JADE platform Personal Agent Infrastructure Plugin Manager User Interface User Model COM Bridge Rule Engine Interface XSB Jess yajxb Xtalks Plugin Mapquest Plugin Buddy List Plugin External Plugins External World

26 UMBC an Honors University in Maryland 26 Xtalks agents Xtalks System Xtalks Interface Xtalks Agent Mapquest Agent Personal Agent (1) FIPA Request Response Protocol FIPA Request Response Protocol Periodic querying Scenarios 1,2 Personal Agent (2) Personal Agent (3) Scenarios 3,4 1 – Xtalks Announcement 2 – User Agent Solicitation 3 – Buddy List 4 – Travel Planning Xtalks System

27 UMBC an Honors University in Maryland 27 (4) Learning Markup Rules Where will Semantic web markup come from? Where will Semantic web markup come from? Created dynamically as web pages are generated from databases (e.g., ITTalks). Created dynamically as web pages are generated from databases (e.g., ITTalks). Annotation editors (e.g., SMORE) Annotation editors (e.g., SMORE) NLP Information extraction apps (e.g., Aerotext) NLP Information extraction apps (e.g., Aerotext) Learning markup for specific domains (e.g., ITTalks) Learning markup for specific domains (e.g., ITTalks) Were experimenting with algorithms to learn to add DAML markup to text documents from a training corpus. Were experimenting with algorithms to learn to add DAML markup to text documents from a training corpus. This, coupled with state-of-the-practice Information Extraction techniques, should support automatic markup of many documents. This, coupled with state-of-the-practice Information Extraction techniques, should support automatic markup of many documents.

28 UMBC an Honors University in Maryland 28 LTD DAML Markup Learning System We started with the Stalker algorithm developed at ISI for learning web scraping rules. The ontology structure constrains where objects are sought (e.g., Location has Room, Building, etc.) Rules are generated with a hill climbing algorithm. Many rules are generated so co-training techniques can be used to mark up plain documents. Results on learning to markup talk announcements are promising.

29 UMBC an Honors University in Maryland 29 (5) IR and the Semantic Web Problem: How do we do information retrieval over documents and queries which combine free text and semantic web markup? Problem: How do we do information retrieval over documents and queries which combine free text and semantic web markup? IR systems and KB systems use different models IR systems and KB systems use different models One Solution: (1) index both the text and markup and then (2) use existing IR systems to find documents that match queries One Solution: (1) index both the text and markup and then (2) use existing IR systems to find documents that match queries Issues: (1) How do we index markup? (2) When and where do we do inferencing over the markup? Issues: (1) How do we index markup? (2) When and where do we do inferencing over the markup? Applications: (1) Improved recall and precision for IR systems, (2) Retrieving documents for question answering. Applications: (1) Improved recall and precision for IR systems, (2) Retrieving documents for question answering.

30 UMBC an Honors University in Maryland 30 Student Event Scenario UMBC sends out descriptions of ~50 events a week to students. UMBC sends out descriptions of ~50 events a week to students. Each student has a standing query used to route event messages. Each student has a standing query used to route event messages. A student only receives announcements of events matching his interests and schedule. A student only receives announcements of events matching his interests and schedule. Use LMCOs AeroText system to automatically add DAML+OIL markup to event descriptions. Use LMCOs AeroText system to automatically add DAML+OIL markup to event descriptions. Categorize text announcements into event types Categorize text announcements into event types Identify key elements and add DAML markup Identify key elements and add DAML markup Use JESS to reason over the markup, drawing ontology supported inferences Use JESS to reason over the markup, drawing ontology supported inferences

31 UMBC an Honors University in Maryland 31 Event Ontology A simple ontology for University events A simple ontology for University events Includes classes, subclasses, properties, etc. Includes classes, subclasses, properties, etc. Can include instance data, e.g., UMBC, NEC, Fairleigh Dickenson, etc Can include instance data, e.g., UMBC, NEC, Fairleigh Dickenson, etc

32 UMBC an Honors University in Maryland 32 IR Engine Were experimenting with two IR engines: JHUs Haircut and UMBCs SIRE, using this technique: Were experimenting with two IR engines: JHUs Haircut and UMBCs SIRE, using this technique: Convert DAML markup to RDF triples Convert DAML markup to RDF triples Infer additional triples which follow from model Infer additional triples which follow from model (S,type,O) ^ (0,subclass,O2) => (S,type,O2) Use domain specific rules to infer additional triples Use domain specific rules to infer additional triples for a movie, retrieve genre property from IMDB web site for a movie, retrieve genre property from IMDB web site Generate 7 indexing terms from each (S,P,O) triple Generate 7 indexing terms from each (S,P,O) triple SPO, SP*, S*O, *PO, S**, *P*, **O Index free text and resulting triple terms Index free text and resulting triple terms

33 UMBC an Honors University in Maryland 33 Indexing triples example We process an event description which we recognize as a showing of a movie with title Spiderman We process an event description which we recognize as a showing of a movie with title Spiderman _j:00255 a movie; title Spiderman. _j:00255 a movie; title Spiderman. Domain specific rules get additional information from the web, such as the movies genre Domain specific rules get additional information from the web, such as the movies genre _j:00255 genre Action. _j:00255 genre Action. That triple yields seven indexing terms: _:j "action. That triple yields seven indexing terms: _:j "action. 1. j00255.owlir.umbc.edu/event/moviegenre.action 2. *.owlir.umbc.edu/event/moviegenre.action 3. j00255.*.action 4. j00255.owlir.umbc.edu/event/moviegenre.* 5. j00255.*.* 6. *.owlir.umbc.edu/event/moviegenre.* 7. **.action

34 UMBC an Honors University in Maryland 34 LMCO AeroText + Java IR Engine Query User Interface Jess Text + triples Event Categories Movie Sport Talk... Trip OWLIR Framework Must OK Must not Results User Interface Final ResultsInference on results Text + triples Jess Classification Info Extraction Extract triples & reason Text+ DAML Agents Text+ DAML Convert triples to index terms Text Extract triples & reason Convert triples to index terms Text Index Expand Event Description Event Descriptions

35 UMBC an Honors University in Maryland 35 DOCUMENT 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001 'UMBC Blood Drive!! Office of Student Life launches its annual Blood Drive for the Red Cross on Mon, Nov 20 in the UC Ballroom from 10am - 4pm. triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001_place', 'http://daml.umbc.edu/ontologies/event_ont#Building', 'University Center'). triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001', 'http://daml.umbc.edu/ontologies/event_ont#Organizer', 'Office of Student Life'). triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001_date', 'http://daml.umbc.edu/ontologies/event_ont#Day_of_week', 'Monday'). …

36 UMBC an Honors University in Maryland 36 QUERY triple(query_001)( 'http://daml.umbc.edu/ontologies/query#query_001, 'http://daml.umbc.edu/ontologies/event_ont#Movie_Name' 'Oceans Eleven'). triple(query_001)( 'http://daml.umbc.edu/ontologies/query#query_001, 'http://daml.umbc.edu/ontologies/event_ont#Organizer SEB').

37 UMBC an Honors University in Maryland 37 Results? Have done initial experiments measuring recall and precision over a small collection of 1500 event announcements and 12 queries. Have done initial experiments measuring recall and precision over a small collection of 1500 event announcements and 12 queries. Compare Compare Only free text Only free text Free text + base triples but no inferencing Free text + base triples but no inferencing Free text + triples + inferred triples Free text + triples + inferred triples Found improved precision and recall Found improved precision and recall Larger experiments needed Larger experiments needed

38 UMBC an Honors University in Maryland 38 (6) Modeling trust policies Theres great interest in modeling and using trust in open systems such as the web and pervasive computing. Theres great interest in modeling and using trust in open systems such as the web and pervasive computing. Trust based systems are good when you have to deal with agents that are not well known authenticated users. Trust based systems are good when you have to deal with agents that are not well known authenticated users. Computing trust is usually Computing trust is usually Based on observed properties of agents Based on observed properties of agents Has a social component (e.g., reputation) Has a social component (e.g., reputation) Weve developed a trust policy language (REI) that uses DAML+OIL as its encoding for (1) agent properties and (2) policy rules. Weve developed a trust policy language (REI) that uses DAML+OIL as its encoding for (1) agent properties and (2) policy rules.

39 UMBC an Honors University in Maryland 39 (4) Delegation Based Model for Distributed Trust We are developing a delegation based model for distributed authorization and trust for use in both wired and wireless scenarios. We are developing a delegation based model for distributed authorization and trust for use in both wired and wireless scenarios. Trust depends on Trust depends on policies + credentials + delegation actions + proofs of permissions and obligations. policies + credentials + delegation actions + proofs of permissions and obligations. Agents make speech acts about and reason over these properties and relations Agents make speech acts about and reason over these properties and relations Grounded in an ontology represented in DAML Grounded in an ontology represented in DAML

40 UMBC an Honors University in Maryland 40 Rei Policy Language Rei includes domain independent ontologies to represent basic concepts: agents, actions, permissions, obligations, prohibitions, delegations, etc. Rei includes domain independent ontologies to represent basic concepts: agents, actions, permissions, obligations, prohibitions, delegations, etc. Users can specify domain dependent ontologies to describe classes, properties and roles of people and agents Users can specify domain dependent ontologies to describe classes, properties and roles of people and agents Includes a policy engine that interprets and reasons over Rei policies Includes a policy engine that interprets and reasons over Rei policies Has been developed in logic (SICStus Prolog) Has been developed in logic (SICStus Prolog) Very powerful reasoning capability Very powerful reasoning capability Relatively straightforward to translate to/from RDF-S (using triples) Relatively straightforward to translate to/from RDF-S (using triples)

41 UMBC an Honors University in Maryland 41 RDF Ontology

42 UMBC an Honors University in Maryland 42 RDF Ontology By extending the appropriate classes of the ontology By extending the appropriate classes of the ontology Actions can be defined Actions can be defined Domain dependent information can be added Domain dependent information can be added Meta policies can be created Meta policies can be created Policies in RDF can be developed Policies in RDF can be developed Current ontologies… Current ontologies… Root Schema Root Schema Root Schema Root Schema Schema for policy objects Schema for policy objects Schema for policy objects Schema for policy objects Schema for speech acts Schema for speech acts Schema for speech acts Schema for speech acts Schema for meta policies Schema for meta policies Schema for meta policies Schema for meta policies

43 UMBC an Honors University in Maryland 43 Resource ReiRoot Policy Rule PolicyRule MetaPolicy Proposition Condition AndCondition OrCondition NotCondition Entity Agent Object Action DomainAction Creator rdf PolicyCondition rdf RulePolicy rdf PolicyRuleActor rdf PolicyRuleCondition rdf PolicyRuleObject rdf ConditionVal rdf AndCondition1 rdf AndCondition2 rdf OrCondition1 rdf OrCondition2 rdf NotCondition1 rdf OwnerOfEntity rdf Affiliation rdf Location rdf ActionName rdf OwnerOfAction rdf Type rdf TargetObject rdf PreCondition rdf Effect rdf PolicyObject Rule Has 'has' used in logic programs, will be removed in rdfs section Right Obligation Dispensation Prohibition PolicyObjectAction rdf PolicyObjectCondition rdf PolicyObjectCommitment rdf Rule From Jon Pastors ppt

44 UMBC an Honors University in Maryland 44 Action SpeechAct Delegation Cancel Request Revoke Sender rdf Receiver rdf Content rdf ReplyWith rdf ReplyBy rdf ReplyTo rdf Literal Entity Agent PolicyObject Speech Act From Jon Pastors ppt

45 UMBC an Honors University in Maryland 45 ModalityPrecedence Overrides PositiveModality NegativeModality PolicyOverrides RuleOverrides SubjectCondition rdf MiscCondition rdf ActionCondition rdf Overridder rdf Overridden rdf Policy MetaPolicy PolicyRule Condition Meta Policy From Jon Pastors ppt

46 UMBC an Honors University in Maryland 46 We envision pervasive computing environments where devices can see, query and inform many data streams and sources in their environment. We envision pervasive computing environments where devices can see, query and inform many data streams and sources in their environment. Traditional mobile data management approaches are insufficient to address the new challenges posed by the data-intensive pervasive computing environments Traditional mobile data management approaches are insufficient to address the new challenges posed by the data-intensive pervasive computing environments Our approach uses both agents and the semantic web Our approach uses both agents and the semantic web Cross layer interaction Cross layer interaction Proactive, (semi-) autonomous peer mobile devices in the network Proactive, (semi-) autonomous peer mobile devices in the network Profiles to describe users, devices and data objects using BDI principles and a semantically rich language (e.g., DAML) Profiles to describe users, devices and data objects using BDI principles and a semantically rich language (e.g., DAML) Negotiation for services resulting in contracts to model both transaction and QOS requirements and commitments Negotiation for services resulting in contracts to model both transaction and QOS requirements and commitments (5) P2P Data Management in Pervasive Computing Environments

47 UMBC an Honors University in Maryland 47 SW and Pervasive computing One of our research foci is mobile computing One of our research foci is mobile computing … In particular, we are interested in advanced pervasive and ubiquitous computing environments … In particular, we are interested in advanced pervasive and ubiquitous computing environments … populated by devices, systems and agents that … populated by devices, systems and agents that are aware of their context, are aware of their context, try to understand what is going on, try to understand what is going on, anticipate our needs and anticipate our needs and actively work to serve us better actively work to serve us better

48 UMBC an Honors University in Maryland 48 Yesterday: Gadgets are Everything Cool toys… Too bad they cant talk to each other…

49 UMBC an Honors University in Maryland 49 Today: Connection is Everything Sync. Download. Done. Configuration? Too much work…

50 UMBC an Honors University in Maryland 50 Tomorrow: Service is Everything Thank God! Everything is done for me!

51 UMBC an Honors University in Maryland 51 Context Aware Pervasive Computing Environment An intelligent context broker acquires context information from devices, agents and sensors in its environment and fuses it into a coherent context model, which is then shared with the devices and their agents.

52 UMBC an Honors University in Maryland 52 An Intelligent Meeting Room The broker detects Alices presence B B The broker builds the context model Web The broker knows Alices role and intention + The broker informs the subscribed agents B A The projector agent setup the presentation

53 UMBC an Honors University in Maryland 53 Why Semantic Web & OWL Everybody can say something about everything Everybody can say something about everything Information that describes resources on the Web is distributed Information that describes resources on the Web is distributed Information that describes people, places & objects in a pervasive context-aware system is distributed Information that describes people, places & objects in a pervasive context-aware system is distributed OWL enables ontology reasoning over dynamic situational information. OWL enables ontology reasoning over dynamic situational information. OWL/XML is probably the most effective representation for machines to process ontology and share knowledge. OWL/XML is probably the most effective representation for machines to process ontology and share knowledge.

54 UMBC an Honors University in Maryland 54 The CoBrA Ontology CoBrA = Context Broker Architecture CoBrA = Context Broker Architecture It attempts to capture a set of common ontologies for describing It attempts to capture a set of common ontologies for describing People, places, devices, agents, services and non-computing objects in an intelligent meeting environment People, places, devices, agents, services and non-computing objects in an intelligent meeting environment The properties and relationships between these entities and the environment The properties and relationships between these entities and the environment It doesnt attempt to be the ontology It doesnt attempt to be the ontology

55 UMBC an Honors University in Maryland 55 The CoBrA Ontology

56 UMBC an Honors University in Maryland 56 (8) Trading Agents Weve build an agent-based environment inspired by TAC, the Trading agent Competition Weve build an agent-based environment inspired by TAC, the Trading agent Competition TAC is a forum promoting research into the trading agent problem with games run in 00, 01, 02, 03 TAC is a forum promoting research into the trading agent problem with games run in 00, 01, 02, 03 TAC agents operate within a travel shopping scenario, buying and selling goods to best serve their clients and are scored based on client's preferences for trips assembled, and minimizing cost. TAC agents operate within a travel shopping scenario, buying and selling goods to best serve their clients and are scored based on client's preferences for trips assembled, and minimizing cost. TAC in organized around a central auction server TAC in organized around a central auction server Our goal is to open up the system, allowing peer-to-peer communication among agents as well various kinds of mediator, auction, discovery, service provider agents. Our goal is to open up the system, allowing peer-to-peer communication among agents as well various kinds of mediator, auction, discovery, service provider agents.

57 UMBC an Honors University in Maryland 57 A Typical Scenario Bulletin Board CA TA Auction Service Airline WS Hotel WS 12a b Market Oversight Agent

58 UMBC an Honors University in Maryland 58 TAGA Agents (1) …. Customer Agents One CA joins the Game every 30 Sec. Hotel Web Service Entertainment Web Service Airline Web Service TA-1 (AAP)TA-2 (AAP)TA-4 (JADE) Find travel arrangements Save $$ Organize travel Maximize profits sell goods Maximize profits

59 UMBC an Honors University in Maryland 59 TAGA Agents (2) Market Oversight Agent Auction Service Agent Helps CA find and engage one or more TA Operates the auctions markets: English, Dutch, Priceline and Hotwire. Manage the financial records Announces the winning TA Bulletin Board Agent

60 UMBC an Honors University in Maryland 60 TAGA in Action TAGA Home Page TAGA on Agentcities net (UMBCTac.agentcities.net)UMBCTac.agentcities.net Download the latest TAGA pkg and docs Create a TAGA game online TAGA supports heterogeneous agent platform. A FIPA-JADE agent can interact with a FIPA-AAP agent

61 UMBC an Honors University in Maryland 61 (and more … new agent, user login, create game, game history) Monitor Customer Agents The TAGA Game Server View TAGA game status View ACL message traffic Monitor Open Market Auction

62 UMBC an Honors University in Maryland 62 TAGA goal and features Goal: an open test bed for research on agents, FIPA, and SW in an ecommerce environment Goal: an open test bed for research on agents, FIPA, and SW in an ecommerce environment Features: Features: Part of the Agentcities network Part of the Agentcities network Everything is a FIPA-compliant agent Everything is a FIPA-compliant agent Supported by OWL ontologies Supported by OWL ontologies Agents use RDF and OWL as for their content language Agents use RDF and OWL as for their content language DAML-S used for service description and discovery DAML-S used for service description and discovery New FIPA compliant protocols for various kinds of auctions New FIPA compliant protocols for various kinds of auctions

63 UMBC an Honors University in Maryland 63 Other UMBC SW work Service composition in pervasive computing environments Service composition in pervasive computing environments SW for Bluetooth SDP (service discovery protocol) SW for Bluetooth SDP (service discovery protocol) Javaspaces with DAML+OIL descriptions instead of flat tuples Javaspaces with DAML+OIL descriptions instead of flat tuples Intelligent opportunistic data caching in mobile computing environments Intelligent opportunistic data caching in mobile computing environments Using DAML-S in FIPAs directory facilitator Using DAML-S in FIPAs directory facilitator

64 UMBC an Honors University in Maryland 64 Conclusions and final thoughts SW might be a chance for us to get some AI out of the lab SW might be a chance for us to get some AI out of the lab Solving the symbol grounding problem Solving the symbol grounding problem Rethinking agent communication Rethinking agent communication How do we get there How do we get there

65 UMBC an Honors University in Maryland 65 The symbol grounding problem An argument against human-like AI is that its impossible unless machines share our perception of the world. An argument against human-like AI is that its impossible unless machines share our perception of the world. A solution to this symbol grounding problem is to give robots with human inspired senses. A solution to this symbol grounding problem is to give robots with human inspired senses. But the world we experience is determined by our senses, and human and machine bodies may lead to different conceptions of the world (e.g. Nagels What Is It Like To Be a Bat? ) But the world we experience is determined by our senses, and human and machine bodies may lead to different conceptions of the world (e.g. Nagels What Is It Like To Be a Bat? ) Maybe the Semantic Web is a way out of this problem? Maybe the Semantic Web is a way out of this problem? MITs Cog

66 UMBC an Honors University in Maryland 66 Solving the symbol grounding problem The web may become a common world that both humans and machines can understand. The web may become a common world that both humans and machines can understand. Confession: the web is more familiar and real to me than much of the real world. Confession: the web is more familiar and real to me than much of the real world. Physical objects can be tagged with low cost (e.g., $0.05) transponders or RFIDs encoding their URIs Physical objects can be tagged with low cost (e.g., $0.05) transponders or RFIDs encoding their URIs See HPs Cooltown project See HPs Cooltown project

67 UMBC an Honors University in Maryland 67 Rethinking the agent communication paradigm Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure. Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure. This paradigm was articulated ~1990, about the same time as the WWW was developed. This paradigm was articulated ~1990, about the same time as the WWW was developed. Our MAS approach has not yet left the laboratory yet the Web has changed the world. Our MAS approach has not yet left the laboratory yet the Web has changed the world. Maybe we should try something different? Maybe we should try something different? The communication MAS paradigm has been peer-to- peer message oriented communication mediated by brokers and facilitators -- an approach inherited from client-server systems. The communication MAS paradigm has been peer-to- peer message oriented communication mediated by brokers and facilitators -- an approach inherited from client-server systems.

68 UMBC an Honors University in Maryland 68 Rethinking the agent communication paradigm A possible new paradigm? Agents publish beliefs, requests, and other speech acts on web pages. Agents publish beliefs, requests, and other speech acts on web pages. Brokers search for and index published content Brokers search for and index published content Agents discover what peers have published on the web and browse for more details Agents discover what peers have published on the web and browse for more details Agents speak for content on web pages by Agents speak for content on web pages by Answering queries about them Answering queries about them Accepting comments and assertions about them Accepting comments and assertions about them

69 UMBC an Honors University in Maryland 69 How do we get there from here? This semantic web emphasizes ontologies – their development, use, mediation, evolution, etc. This semantic web emphasizes ontologies – their development, use, mediation, evolution, etc. It will take some time to really deliver on the agent paradigm, either on the Internet or in a pervasive computing environment. It will take some time to really deliver on the agent paradigm, either on the Internet or in a pervasive computing environment. The development of complex systems is basically an evolutionary process. The development of complex systems is basically an evolutionary process. Random search carried out by tens of thousands of researchers, developers and graduate students. Random search carried out by tens of thousands of researchers, developers and graduate students.

70 UMBC an Honors University in Maryland 70 Climbing Mount Improbable The sheer height of the peak doesn't matter, so long as you don't try to scale it in a single bound. Locate the mildly sloping path and, if you have unlimited time, the ascent is only as formidable as the next step. -- Richard Dawkins, Climbing Mount Improbable, Penguin Books, 1996.

71 UMBC an Honors University in Maryland 71 The Evolution of Useful Things The Evolution of Useful Things, Henry Petroski, The Evolution of Useful Things, Henry Petroski, Prior to the 1890s, papers were held together with straight pens. Prior to the 1890s, papers were held together with straight pens. The development of spring steel allowed the invention of the paper clip in The development of spring steel allowed the invention of the paper clip in It took about 25 years (!) for the evolution of the modern gem paperclip, considered to be optimal for general use. It took about 25 years (!) for the evolution of the modern gem paperclip, considered to be optimal for general use.

72 UMBC an Honors University in Maryland 72 So, we should … Start with the simple and move toward the complex Start with the simple and move toward the complex E.g., from vocabularies to FOL theories E.g., from vocabularies to FOL theories Allow many ontologies to bloom Allow many ontologies to bloom Let natural evolutionary processes select the most useful as common consensus ontologies. Let natural evolutionary processes select the most useful as common consensus ontologies. Support diversity in ontologies Support diversity in ontologies Monocultures are unstable Monocultures are unstable There should be no THE ONTOLOGY FOR X. There should be no THE ONTOLOGY FOR X. The evolution of powerful, machine readable ontologies will take many years, maybe generations The evolution of powerful, machine readable ontologies will take many years, maybe generations Incremental benefits will more than pay for effort Incremental benefits will more than pay for effort

73 UMBC an Honors University in Maryland 73 For more information On our work at UMBC On our work at UMBC ITTALKS ITTALKS TAGA TAGAhttp://taga.umbc.edu/

74 UMBC an Honors University in Maryland 74

75 UMBC an Honors University in Maryland 75 (3) Enhancing Bluetooths Service Discovery Protocol Bluetooths SDP is very simple Bluetooths SDP is very simple Services and attributes represented by UUIDs which are 128 bit numbers! Services and attributes represented by UUIDs which are 128 bit numbers! No registration, aggregation, multicasting, event notification No registration, aggregation, multicasting, event notification Enhanced SDP uses DAML+OIL Enhanced SDP uses DAML+OIL We assume at least one resource rich device in the ad hoc network to serve as a matchmaker We assume at least one resource rich device in the ad hoc network to serve as a matchmaker Services and attributes described in DAML using a standard ontology Services and attributes described in DAML using a standard ontology All available information from service and attribute descriptions used for matching All available information from service and attribute descriptions used for matching Reasons to obtain closest match Reasons to obtain closest match

76 UMBC an Honors University in Maryland 76 Intrusion Detection Jeffrey Undercoffer Jeffrey Undercoffer Distributed Intrusion Detection Services Distributed Intrusion Detection Services Data Mining over low level attributes at the following levels: Data Mining over low level attributes at the following levels: Process Process System System Network Network Secure framework for inter process communications Secure framework for inter process communications Define a Victim-Centric Ontology Define a Victim-Centric Ontology Formal theorem prover to reason over instances of the ontology Formal theorem prover to reason over instances of the ontology Develop a statistical model, using the Kullback-Liebler dissimilarity measure, for analyzing streams of system calls Develop a statistical model, using the Kullback-Liebler dissimilarity measure, for analyzing streams of system calls

77 UMBC an Honors University in Maryland 77 MoGATU Filip Perich Filip Perich Addressing the issues of data management in pervasive computing environments Addressing the issues of data management in pervasive computing environments Use semantic language for annotating data and providers Use semantic language for annotating data and providers Discovery of data and data sources Discovery of data and data sources Data dissemination models Data dissemination models Collaboration between devices for processing queries over multiple streams (network joins) Collaboration between devices for processing queries over multiple streams (network joins) Transactional support for preserving (local) consistency state Transactional support for preserving (local) consistency state Profiles for enabling devices to proactively acquire and cache data for future use Profiles for enabling devices to proactively acquire and cache data for future use Supported by NSF and DARPA awards Supported by NSF and DARPA awards Information Generator Y Information Provider X InforMa Information Provider and Instance Metadata Routing Information Bluetooth.Interface User.Interface b.Interface

78 UMBC an Honors University in Maryland 78 Service Discovery and Composition Dipanjan Chakraborty Dipanjan Chakraborty Develop a peer-to-peer caching based distributed service discovery mechanism Develop a peer-to-peer caching based distributed service discovery mechanism Caching of neighboring services Caching of neighboring services Selective forwarding of requests Selective forwarding of requests Broker-based Service Composition Broker-based Service Composition Dynamic Broker selection based mechanism Dynamic Broker selection based mechanism Distributed Broker-based mechanism Distributed Broker-based mechanism Utilizes the peer-to-peer service discovery layer Utilizes the peer-to-peer service discovery layer Source-monitored fault-tolerance Source-monitored fault-tolerance


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