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A Brief Overview of A Brief Overview of Agent Communication Agent Communication
in the in the Semantic Web EraSemantic Web Era-- and Beyond ---- and Beyond --
Tim FininTim FininUniversity of Maryland, Baltimore County
April 2007
http://ebiquity.umbc.edu/resource/html/id/220/
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Overview
• Agent communication languages• 1990-2000 DARPA knowledge sharing
effort• 1997-2002 FIPA• 2000- (Semantic) Web• 2010- and beyond• Are we making progress?
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Agent Communication• Agent-to-agent communication is key to realizing
the potential of the agent paradigm, just as the development of human language was key to the development of human intelligence and societies.
• Agents use an Agent Communication Language (ACL) to communication information and knowledge.
• Genesereth (CACM 1994) defined a software agent as any system which uses an ACL to exchange information.
Genesereth, M. R., Ketchpel, S. P.: “Software Agents”, Communications of the Association for Computing Machinery, July 1994, pp 48-53.
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Some ACLs•Knowledge sharing approach
– KQML, KIF, Ontologies
•FIPA•Ad hock languages
– e.g., SRI’s OAA
Shared objects, procedure callsand data structures
Shared facts, rules, constraints, procedures and knowledge
Shared beliefs, plans, goals,intentions, policies …
?? SharedExperiences &Strategies ??
e.g., CORBA, RPC, RMI
e.g., KQML, FIPA, KIF, Aglets, OWL
e.g., team theories,joint intentions, …
KnowledgeSharing
IntentionalSharing
?
ObjectSharing
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BDI Agents, Theories and Architectures
• BDI architectures describe the internal state of an agent by the mental states of beliefs, goals and intentions
• BDI theories provide a conceptual model of the knowledge, goals, and commitments of an agent
• BDI agents have some (implicit or explicit) representations of the corresponding attitudes
• BDI models are important in defining the semantics of ACLs
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BDI Model and Communication
B + D => I
I => A
B + D => II => A
• Communication is a means to (1) reveal to others what our BDI state is and (2) attempt to effect the BDI state of others.
• Note the recursion: an agent has beliefs about the world, beliefs about other agents, beliefs about the beliefs of other agents, beliefs about the beliefs another agent has about it, ...
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1990-2000 1990-2000 Knowledge Knowledge
Sharing EffortSharing Effort
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Historical Note:Knowledge Sharing Effort
• Initiated by DARPA circa 1990 with later support from NSF, AFOSR, etc.– Participation by ~100 researchers in academia and industry
• Developing techniques, methodologies and software tools for knowledge sharing and knowledge reuse.
• Sharing and reuse can occur at design, implementation or execution time.
• Mostly wound down by ~2000 as funding dried up and industry failed to adopt the ideas
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Knowledge Sharing Effort• Knowledge sharing requires a communication • … which requires a common language• We can divide a language into syntax, semantics, and
pragmatics• Some existing components that can be used independently or
together:
– KIF - knowledge Interchange Format (syntax)– Ontolingua - a language for defining
sharable ontologies (semantics)– KQML - a high-level interaction
language (pragmatics)
Propositional
Propositionalattitudes
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Knowledge Interchange Format
• KIF ~ First order logicwithset theory
• An interlingua for encoded declarative knowledge– Takes translation among n
systems from O(n2) to O(n)
• Common language for reusable knowledge– Implementation independent semantics– Highly expressive - can represent knowledge in typical application KBs.– Translatable - into and out of typical application languages– Human readable - good for publishing reference models and ontologies.
• 2003: KIF superceded by Common Logic (http://cl.tamu.edu/)
– http://en.wikipedia.org/wiki/Common_Logic
• Semantic Web languages RDF and OWL are also alternatives
Know. Basein
Lang1
KIF <-> Lang1 Translator
Sys 1Know. Base
inLang2
KIF <-> Lang2 Translator
Sys 2
Know. Basein KIF
Library
Know. Basein
Lang3
Sys 3
KIF <-> Lang3 Translator
KIF
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KIF Syntax and Semantics• Extended version of first order predicate logic• Simple list-based linear ASCII syntax, e.g.,
(forall ?x (=> (P ?x) (Q ?x)))(exisits ?person (mother mary ?person))(=> (apple ?x) (red ?x))(<<= (father ?x ?y) (and (child ?x ?y) (male ?x))(=> (believes john ?p) (believes mary ?p)) (believes john '(material moon stilton))
• Model-theoretic semantics• KIF includes an axiomatic specification of large
function and relation vocabulary and a vocabulary for numbers, sets, and lists
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Common Semantics Shared Ontologies and Ontolingua
• Ontology: A common vocabulary and agreed upon meanings to describe a subject domain.
• Ontolingua is a language for building, publishing, and sharing ontologies.– A web-based interface to a browser/editor server.– Ontologies can be automatically translated into
other content languages, including KIF, LOOM, Prolog, etc.
– The language includes primitives for combining ontologies.
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Common PragmaticsKnowledge Query and Manipulation Language
• KQML is a high-level, message-oriented, communication language and protocol for information exchange independent of content syntax and ontology.
• KQML is also independent of – transport mechanism, e.g., tcp/ip, email, corba, IIOP, http
...– High level protocols, e.g., Contract Net, Auctions, …
• Each KQML message represents a single speech act (e.g., ask, tell, achieve, …) with an associated semantics and protocol.
• KQML includes primitive message types of particular interest to building interesting agent architectures (e.g., for mediators, sharing intentions, etc.)
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Common High-level Protocols• There is also a need for communication agents to agree on
the agent-level protocols they will use.• The protocol is often conveyed via an extra parameter on a
message– (ask :from Alice :to Bob … :protocol auction42 …)
• Common protocols:– Contract net– Various auction protocols– Name registration
• These protocols are often defined in terms of constraints on possible conversations and can be expressed as– Grammars (e.g., DFAs, ATNs, DCGs…)– Petri networks– UML-like interaction (activity) diagrams– Conversation plans– Rules or axioms
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Common Service Infrastructure• Many agent systems assume a common set of
services such as:– Agent Name Sever– Broker or Facilitator– Communication visualizer– Certificate server
• These are often tied rather closely to an ACL since a given service is implemented to speak a single ACL
• Moreover, some of the services (e.g., name registration) may be logically ACL-dependent– e.g., Some ACLs don’t have a notion of an agent’s name
and others have elaborate systems of naming
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A KQML Message
Represents a single speech act or performative ask, tell, reply, subscribe, achieve, monitor, ...
with an associated semantics and protocol tell( i,j, Bi ) = fp[Bi Bi Bi( Bifj Bi Uifj Bi )] re[Bj Bi] ...
and a list of attribute/value pairs:content, :language, :from, :in-reply-to
(tell :sender bhkAgent :receiver fininBot :in-reply-to id7.24.97.45391 :ontology ecbk12 :language Prolog :content “price(ISBN3429459,24.95)”)
performative
parameter
value
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Performatives (1997)
DenySubscribe
KQMLPerformatives
RequestQuery
Meta
Promise
Inform
Inform
DB Basic
AchieveUnachieve
AdvertiseUnadvertise
Stream
Cursor
Basic
Goal
Network
FacilitationBroker-oneRecommend-oneRecruit-oneBroker-allRecommend-allRecruit-all
BroadcastForward
TellUntell
InsertUninsertDelete-oneDelete-allUndelete
StreamEos
Ask-ifAsk-oneAsk-all
StreamEos
Reply
StandbyReadyNextRestDiscard
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Simple Query Performatives
A B
ask-one(P)
tell(P)
ask-all(P)
tell((p1 p2 p3...))
• The ask-one, ask-all, ask-if, and stream-all performatives provide a basic query mechanism.
A B
ask-if(P)
Sorry
Stream-all(P)
tell(P1)
tell(P2)
tell(P3)eos
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Capability Description
A BFACC
advertise(q2)ask-all(advertise(P)
advertise(p2)advertise(p1)
advertise(q1)
advertise(q3)
The advertise performative is used to describe the performatives an agent is prepared to accept.
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Facilitation Performatives
C
broker(ask(P))
B
advertise(ask(P))
ask(P)
tell(P)tell(P)
A
Broker
C
recruit(ask(P))
B
advertise(ask(P))
ask(P)
tell(P)
A
Recruit
C
recommend(ask(P))
B
adv(ask(P))
tell(P)
ask(P)fwd(adv(ask(P)))
A
Recommend
The three facilitation performatives come in a X-one and X-all versions:
•Broker-one and broker-all
•Recruit-one and recruit-all
•recommend-one and recommend-all
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Ontology languages vary in expressivity
Catalog/ID
GeneralLogical
constraints
Terms/glossary
Thesauri“narrower
term”relation
Formalis-a
Frames(properties)
Informalis-a
Formalinstance
Value Restriction
Inverse, Disjointness,
part of…
After Deborah L. McGuinness (Stanford)After Deborah L. McGuinness (Stanford)
SimpleTaxonomies
ExpressiveOntologies
Wordnet
CYCRDF DAML
OO
DB Schema RDFS
IEEE SUOOWL
UMLS
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Conceptual Schemas
Table: price *stockNo: integer; cost: float
139 74.50140 77.60… …
Data Base:
Data Base Schema:
Conceptual Schema:
A conceptual schema specifies the intended meaning of concepts used in a data base
AutoProduct
Ontology
ProductOntology
Units &MeasuresOntology
price(x, y) => (x’, y’) [auto_part(x’) & part_no(x’) = x & retail_price(x’, y’, Value-Inc) & magnitude(y’, US_dollars) = y]
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1997-20031997-2003StandardizationStandardization
FIPAFIPA
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What is FIPA• http://fipa.org/• The Foundation for Intelligent Physical Agents
founded as a non-profit association ~1997.• FIPA’s purpose is to promote the success of
emerging agent-based applications, services and equipment by establishing standards– MP3 was the model
• In 2006 it became an IEEE standards committee
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FIPA Agent Communication Language• Called FIPA ACL• Based on speech acts• Messages are actions (communicative actions or CAs)• Communicative acts are described in both a narrative form
and a formal semantics based on modal logic• Syntax is similar to KQML• Specification provides a normative description of high-
level interaction protocols (aka conversations)• Separate library of protocols and content languages
(e.g., SL, KIF, RDF)• Several serializations
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Agent-Standardization - FIPA Cooperation between Agents
CAs for Information Exchange• proposition or reference as content• Basic CAs:
– inform – query-ref– not-understood
• Advanced CAs:– inform-if, inform-ref– confirm, disconfirm– subscribe
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Agent-Standardization - FIPA Cooperation between Agents
CAs for task delegation• action-description as content• Basic CAs:
– request– agree– refuse– failure– not-understood
• Advanced CAs:– request-when, request-whenever– cancel
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Agent-Standardization - FIPA Cooperation between Agents
CAs for Negotiation• action-description and proposition as content• Initiating CA
– cfp
• Negotiating CA– propose
• Closing CAs– accept-proposal– reject-proposal
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Agent-Standardization - FIPA Cooperation between Agents
Example(request
:sender (:name [email protected]:3410):receiver (:name hilton_hotel@tcp://hilton.com:5001):ontology fipa-pta:language SL:protocol fipa-request:content( action hilton_hotel@tcp://hilton.com:5001 ( book-hotel (:arrival 04/07/1999) (:departure 12/07/1999)
(:infos ( )) )))
FIPA 99: other possibilities to define content!
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Agent-Standardization - FIPA Cooperation between Agents
FIPA Cooperation • CAs have their own formal semantics
– difficult to implement– need not be implemented - agent must behave
according to semantics
• Interaction protocols define structured conversations – based on CAs– basis for dialogues between agents– basic set of pre-defined IPs– own IPs can be defined
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query
not-understood inform
Agent-Standardization - FIPA Cooperation between Agents
FIPA-Query (simplified - for information exchange)
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Agent-Standardization - FIPA Cooperation between AgentsAgent-Standardization - FIPA Cooperation between Agents
request(action)
not-understood agreerefuse(reason)
failure(reason) inform-refinform(done())
FIPA-Request - for task delegation
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AUML
• Agent UML• http://www.auml.org/• ULM like framework
for specifying agent communication and interaction protocols
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FIPA Agent Platform
AMS DF ACC
internal platform message transport
AAsoftware
IIOP
Agents belong to one or more agent platforms which provide basic services.
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JadeJava Agent Development Framework is an OS software framework for multi-agent systems, implemented in Java.
– Developed by Telcom Italia– Built on FIPA standards– Libraries (LEAP) for handheld
and wireless devices– http://jade.tilab.com/
System of choice for building FIPA based MAS April 2007
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2000-?2000-?Semantic WebSemantic Web
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“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.
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“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)
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“The Semantic Web will globalize KR, just as the WWW globalize hypertext”
-- Tim Berners-Lee
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OriginsTim Berners-Lee’s original 1989 WWW proposal described a web of relationships among namedobjects unifying many info. management tasks. Capsule history• Guha’s MCF (~94)
• XML+MCF=>RDF (~96)
• RDF+OO=>RDFS (~99)
• RDFS+KR=>DAML+OIL (00)
• W3C’s SW activity (01)
• W3C’s OWL (03)
http://www.w3.org/History/1989/proposal.html
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W3C’s Semantic Web Goals
Focus on machine consumption:
"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation."
-- Berners-Lee, Hendler and Lassila, The Semantic Web, Scientific American, 2001
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Agents?
• DARPA gave the Semantic Web a big push starting in 2000– Going from simple RDF to OWL
• DARPA Agent Markup Language• Goal was to give agents access to information and
knowledge• And to populate the web with intelligent agents
providing services
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TBL’s semantic web vision
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RDF is the first SW language
<rdf:RDF ……..> <….> <….></rdf:RDF>
XML EncodingGraph
stmt(docInst, rdf_type, Document)stmt(personInst, rdf_type, Person)stmt(inroomInst, rdf_type, InRoom)stmt(personInst, holding, docInst)stmt(inroomInst, person, personInst)
Triples
RDFData Model
Good for Machine
Processing
Good For HumanViewing
Good For Reasoning
RDF is a simple language for building graph based representations
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Simple RDF Examplehttp://umbc.edu/
~finin/talks/idm02/“Intelligent Information Systemson the Web and in the Aether”
http://umbc.edu/
dc:Title
dc:Creator
bib:Aff
“Tim Finin” “[email protected]”
bib:namebib:email
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XML encoding for RDF<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:bib="http://daml.umbc.edu/ontologies/bib/"><description about="http://umbc.edu/~finin/talks/idm02/"> <dc:title>Intelligent Information Systems on the Web and in the Aether</dc:Title> <dc:creator> <description> <bib:Name>Tim Finin</bib:Name> <bib:Email>[email protected]</bib:Email> <bib:Aff resource="http://umbc.edu/" /> </description> </dc:Creator></description></rdf:RDF>
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A usecase: FOAF• FOAF (Friend of a Friend) is a simple ontology to describe people and their
social networks.– See the foaf project page: http://www.foaf-project.org/
• We recently crawled the web and discovered over 1,000,000 valid RDF FOAF files.– Most of these are from the http://liveJournal.com/ blogging system which encodes basic
user info in foaf– See http://apple.cs.umbc.edu/semdis/wob/foaf/
<foaf:Person><foaf:name>Tim Finin</foaf:name><foaf:mbox_sha1sum>2410…37262c252e</foaf:mbox_sha1sum><foaf:homepage rdf:resource="http://umbc.edu/~finin/" /><foaf:img rdf:resource="http://umbc.edu/~finin/images/passport.gif" />
</foaf:Person>
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FOAF: why RDF? Extensibility!
• FOAF vocabulary provides 50+ basic terms for making simple claims about people
• FOAF files can use other RDF terms too: RSS, MusicBrainz, Dublin Core, Wordnet, Creative Commons, blood types, starsigns, …
• RDF guarantees freedom of independent extension– OWL provides fancier data-merging facilities
• Result: Freedom to say what you like, using any RDF markup you want, and have RDF crawlers merge your FOAF documents with other’s and know when you’re talking about the same entities.
After Dan Brickley, [email protected]
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RDF Schema (RDFS)• RDF Schema adds
taxonomies forclasses & properties
– subClass and subProperty
• and some metadata.
– domain and rangeconstraints on properties
• Several widely usedKB tools can importand export in RDFS
Stanford Protégé KB editor
• Java, open sourced•extensible, lots of plug-ins•provides reasoning &
server capabilities
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RDFS supports simple inferences
• An RDF ontology plus some RDF statements may imply additional RDF statements.
• This is not true of XML.• Note that this is part of the data model and not of the accessing or
processing code.
@prefix rdfs: <http://www.....>.@prefix : <genesis.n3>.
parent rdfs:domain person; rdfs:range person.mother rdfs:subProperty parent;
rdfs:domain woman;eve mother cain.
parent a property.person a class.woman subClass person.mother a property.eve a person; a woman; parent cain.cain a person.
New and Improved!100% Betterthan XML!!
New and Improved!100% Betterthan XML!!
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W3C’s Web Ontology Language (OWL)
• DAML+OIL begat OWL.• OWL released as W3C recommendation 2/10/04• See http://www.w3.org/2001/sw/WebOnt/ for OWL
overview, guide, specification, test cases, etc. • Three layers of OWL are defined of decreasing levels of
complexity and expressiveness – OWL Full is the whole thing – OWL DL (Description Logic) introduces
restrictions– OWL Lite is an entry level language
intended to be easy to understandand implement
OWL
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OWL in One Slide
<rdf:RDF xmlns:rdf ="http://w3.org/22-rdf-syntax-ns#" xmlns:rdfs=http://w3.org/rdf-schema#>
xmlns:owl="http://www.w3.org/2002/07/owl#”> <owl:Ontology rdf:about=""> <owl:imports rdf:resource="http://owl.org/owl+oil"/></owl:Ontology><owl:Class rdf:ID="Person"> <rdfs:subClassOf rdf:resource="#Animal"/> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty rdf:resource="#hasParent"/> <owl:allValuesFrom rdf:resource="#Person"/> </owl:Restriction> </rdfs:subClassOf> <rdfs:subClassOf> <owl:Restriction owl:cardinality="1"> <owl:onProperty rdf:resource="#hasFather"/> </owl:Restriction> </rdfs:subClassOf> </owl:Class><Person rdf:about=“http://umbc.edu/~finin/"> <rdfs:comment>Finin is a person.</rdfs:comment></Person>
OWL is built on top of XML and RDF
It can be used to add metadata about anything which has a URI.
everything has a URI
OWL is ~= a frame based knowledge representation language
It allows the definition, sharing, composition and use of ontologies
URIs are a W3C standard generalizing URLs
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RDF is being used!• RDF has a solid specification• RDF is being used in a number of web standards
– CC/PP (Composite Capabilities/Preference Profiles), P3P (Platform for Privacy Preferences Project), RSS (RDF Site Summary), RDF Calendar (~ iCalendar in RDF)
• And in other systems– Netscape’s Mozilla web browser, open directory (http://dmoz.org/)
– Adobe products via XMP (eXtensible Metadata Platform)
– Web communities: LiveJournal, Ecademy, and Cocolog
– In Microsoft’s VISTA: Connected Services Framework uses an RDF database and SPARQL
– Oracle’s 10g and 11g products
– Yahoo’s food portal
– Joost TV over the web startup
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SPARQL ExampleBASE <http://example.org/>PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>PREFIX foaf: <http://xmlns.com/foaf/0.1/>PREFIX ex: <properties/1.0#>SELECT DISTINCT $person ?name $ageFROM <http://rdf.example.org/people.rdf>WHERE { $person a foaf:Person ; foaf:name ?name. OPTIONAL { $person ex:age $age } . FILTER ! REGEX(?name, "Bob") }LIMIT 3 ORDER BY ASC[?name]
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Some applications involving
ACLs and the Semantic Web
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ITTALKS Architecture
Web server + Java servlets
DAMLreasoning
engine
DAMLreasoning
engine
<daml></daml>
<daml></daml>
<daml></daml>
<daml></daml>
DAML files
Agents
Databases
People
RDBMSRDBMSDB
Email, HTML, SMS, WAP
FIPA ACL, KQML, DAML
SQL
HTTP, KQML, DAML, Prolog
MapBlast, CiteSeer,Google, …
HTTP
HTTP, WebScraping
Web Services
ApacheTomcat
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Travel Agent Game in Agentcities
http://taga.umbc.edu/
TechnologiesFIPA (JADE, April Agent Platform)
Semantic Web (RDF, OWL)
Web (SOAP,WSDL,DAML-S)
Internet (Java Web Start )
FeaturesOpen Market FrameworkAuction ServicesOWL message contentOWL OntologiesGlobal Agent Community
Acknowledgements: DARPA contract F30602-00-2-0591 and Fujitsu Laboratories of America.Students: Y. Zou, L. Ding, H. Chen, R. Pan. Faculty: T. Finin, Y. Peng, A. Joshi, R. Cost. 4/03
MotivationMarket dynamicsAuction theory (TAC)Semantic webAgent collaboration (FIPA & Agentcities)
Travel Agents
Auction Service Agent
Customer Agent
Bulletin BoardAgent
Market Oversight Agent
Request
Direct Buy
Report Direct Buy Transactions
BidBid
CFP
Report Auction Transactions
Report Travel Package
Report Contract
Proposal
Web Service Agents
Ontologieshttp://taga.umbc.edu/ontologies/
travel.owl – travel concepts
fipaowl.owl – FIPA content lang.
auction.owl – auction services
tagaql.owl – query language
FIPA platform infrastructure services, including directory facilitators enhanced to use DAML-S for service discovery
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http://ebiquity.umbc.edu/• Our research group’s web site
generate both HTML and OWL.• HOW? This is relatively easy since
the content is in a database.• PHP is sufficient for the job.• HTML pages have links to
corresponding OWL• WHY? This exposes the
information to programs and agents – no more web scraping.
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CMU MyCampus Project
• Objective: Enhance campus life through context-aware services accessible over the WLAN
• Ontologies– Personal/contextual: location,
calendar, organizational etc.– Privacy preferences: who has
access to what, “obfuscation” rules
– Web services: automated service identification and access (OWL-S)
http://www.cs.cmu.edu/~sadeh/mycampus.htm#Video
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Fujitsu Task Computing
• Objective: Make computing available throughout the physical environment while it is effectively invisible to the users
Play Jeff’s VideoDial Contact from OutlookWeather Info of FLA, CP…
OS/Application
Jeff’s Video
Device
Video from DVVideo from DV Add into OutlookDial
Play (Video)Play (Audio)
Open Save Print
View Contact from OutlookJeff’s Video
OS/ApplicationDevices
Add into OutlookDial
Play (Video)Play (Audio)
Open Save Print
View Contact from Outlook
e-Services
Aerial Photo of Weather Info of
Web Pages
Aerial Photo of Weather Info of
http://www.taskcomputing.org/
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The Context Broker Architecture
Knowledge sharing
Access to more information
Policy
http://cobra.umbc.edu/
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The EasyMeeting System
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An EasyMeeting Scenario
People enter the conference room
They “beam” their policy to the broker
B B
The broker buildsthe context model
Web
The broker detects people presence
B »»»
Alice’s policy says, “inform my personal agent of my location”
AB .. isLocatedIn ..
The broker tells herlocation to her agent
A
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An EasyMeeting Scenario
Her agent informs the broker about her role and intentions
+
Alice’s policy says, “can share with any agents in the room”
A
The broker informsthe subscribed agents
B
The Greeting Srv. greetsAlice & the others
Hello! [xyz]
When all expected participants hv arrived
OFF
DIM
The projector agent sets up the slides
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The SOUPA Ontology
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2010-2010-and Beyondand Beyond
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It's hard to make predictions, especially about the future
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Things to watch
• Google (e.g., GoogleBase)
• Wikipedia (e.g., Semantic MediaWiki)
• Freebase (OWL meets Wikipedia?)
• Joost – a high profile startup (internet meets TV) is using RDF and considers it to be "XML on steroids."
• If RDF is the new KIF, then SPARQL might evolve into the new KQML
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ConclusionsConclusions
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Some key ideas
• Software agents offer a new paradigm for very large scale distributed heterogeneous applications.
• The paradigm focuses on the interactions of autonomous, cooperating processes which can adapt to humans and other agents.
• Agent Communication Languages are a key enabling technology– Mobility is an orthogonal characteristic which many, but not all,
consider central.– Intelligence is always a desirable characteristic but is not strictly
required by the paradigm.
• The paradigm is still forming and ACLs will continue to evolve.