A Brief Overview of Agent Communication in the Semantic Web Era -- and Beyond --

1
A Brief Overview of Agent Communication in the
Semantic Web Era-- and Beyond --

• Tim Finin
• University of Maryland, Baltimore County
• April 2007

http//ebiquity.umbc.edu/resource/html/id/220/
2
Overview

• Agent communication languages
• 1990-2000 DARPA knowledge sharing effort
• 1997-2002 FIPA
• 2000- (Semantic) Web
• 2010- and beyond
• Are we making progress?

3
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.

4
Some ACLs

• Knowledge sharing approach
• KQML, KIF, Ontologies
• FIPA
• Ad hock languages
• e.g., SRIs OAA

?? Shared Experiences Strategies ??
?
e.g., team theories,joint intentions,
Shared beliefs, plans, goals,intentions,
policies
Intentional Sharing
e.g., KQML, FIPA, KIF, Aglets, OWL
Shared facts, rules, constraints, procedures and
knowledge
Knowledge Sharing
Shared objects, procedure calls and data
structures
Object Sharing
e.g., CORBA, RPC, RMI
5
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

6
BDI Model and Communication

• 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, ...

7
1990-2000 Knowledge Sharing Effort
8
Historical NoteKnowledge 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

9
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
Propositional attitudes
10
Knowledge Interchange Format

• KIF First order logicwithset theory
• An interlingua for encoded
  declarative knowledge
• Takes translation among nsystems 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

11
KIF Syntax and Semantics

• Extended version of first order predicate logic
• Simple list-based linear ASCII syntax, e.g.,
• (forall ?x (gt (P ?x) (Q ?x)))
• (exisits ?person (mother mary ?person))
• (gt (apple ?x) (red ?x))
• (ltlt (father ?x ?y) (and (child ?x ?y) (male ?x))
• (gt (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

12
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.

13
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.)

14
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

15
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 dont have a notion of an agents
  name and others have elaborate systems of naming

16
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? ) fpBi Bi? ? ? Bi( Bifj Bi? ?
  Uifj Bi? ) ? reBj Bi? ...
• and a list of attribute/value pairs
• content, language, from, in-reply-to

17
Performatives (1997)
Insert Uninsert Delete-one Delete-all Undelete
Tell Untell
Inform
Basic
DB
Broadcast Forward
Inform
Ask-if Ask-one Ask-all
Network
Basic
Achieve Unachieve
Goal
Request
Query
Stream
Stream Eos
KQML Performatives
Facilitation
Cursor
Standby Ready Next Rest Discard
Broker-one Recommend-one Recruit-one Broker-all Re
commend-all Recruit-all
Reply
Promise
Stream Eos
Advertise Unadvertise
Meta
Deny Subscribe
18
Simple Query Performatives
tell(P2)
tell(P3)
eos

• The ask-one, ask-all, ask-if, and stream-all
  performatives provide a basic query mechanism.

19
Capability Description
The advertise performative is used to describe
the performatives an agent is prepared to accept.
20
Facilitation Performatives

• 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

21
Ontology languages vary in expressivity
Thesauri narrower term relation
space of current interest
Inverse, Disjointness,part of
Frames (properties)
Formal is-a
Catalog/ID
CYC
RDF
DAML
DB Schema
RDFS
UMLS
Wordnet
OO
IEEE SUO
OWL
General Logical constraints
Formal instance
Informal is-a
Value Restriction
Terms/ glossary
SimpleTaxonomies
ExpressiveOntologies
After Deborah L. McGuinness (Stanford)
22
Conceptual Schemas

• A conceptual schema specifies the intended
  meaning of concepts used in a data base

Data Base
Data Base Schema
Table price stockNo integer cost float
Auto Product Ontology
price(x, y) gt ? (x, y) auto_part(x)
part_no(x) x
retail_price(x, y, Value-Inc)
magnitude(y, US_dollars) y
Product Ontology
Conceptual Schema
Units Measures Ontology
23
1997-2003StandardizationFIPA
24
What is FIPA

• http//fipa.org/
• The Foundation for Intelligent Physical Agents
  founded as a non-profit association 1997.
• FIPAs 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

25
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26
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27
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

28
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

29
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

30
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

31
Agent-Standardization - FIPA Cooperation between
Agents

• Example
• (request
• sender (name user_agent_at_bond.mchp.siemens.de
  3410)
• receiver (name hilton_hotel_at_tcp//hilton.com50
  01)
• ontology fipa-pta
• language SL
• protocol fipa-request
• content
• ( action hilton_hotel_at_tcp//hilton.com5001
• ( book-hotel (arrival 04/07/1999)
  (departure 12/07/1999)
• (infos ( ))
• )))
• FIPA 99 other possibilities to define content!

32
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

33
Agent-Standardization - FIPA Cooperation between
Agents

• FIPA-Query (simplified - for information exchange)

query
inform
not-understood
34
Agent-Standardization - FIPA Cooperation between
Agents

• FIPA-Request - for task delegation

request(action)
not-understood
agree
refuse(reason)
failure(reason)
inform-ref
inform(done())
35
AUML

• Agent UML
• http//www.auml.org/
• ULM like framework for specifying agent
  communication and interaction protocols

36
FIPA Agent Platform
Agents belong to one or more agent platforms
which provide basic services.
37
Jade

• Java 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
38
2000-?Semantic Web
39

• 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.

40

• 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)

41

• The Semantic Web will globalize KR, just as the
  WWW globalize hypertext
• -- Tim Berners-Lee

42

• The multi-agent systems paradigm and the web
  both emerged around 1990. One has succeeded
  beyond imagination and the other has not yet made
  it out of the lab.
• -- Anonymous, 2001

43
Origins

• Tim Berners-Lees original 1989 WWW proposal
  described a web of relationships among
  namedobjects unifying many info. management
  tasks.
• Capsule history
• Guhas MCF (94)
• XMLMCFgtRDF (96)
• RDFOOgtRDFS (99)
• RDFSKRgtDAMLOIL (00)
• W3Cs SW activity (01)
• W3Cs OWL (03)

• http//www.w3.org/History/1989/proposal.html

44
W3Cs 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

45
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

46
TBLs semantic web vision
47
Why is this hard?
after Frank van Harmelenand Jim Hendler
48
What a web page looks like to a machine
after Frank van Harmelenand Jim Hendler
49
OK, so HTML is not helpful
Maybe we can tell the machine what the different
parts of the text represent?
title
speaker
time
location
abstract
biosketch
host
50
XML to the rescue?
XML fans propose creating a XML tag set to use
for each application. For talks, we can choose
lttitlegt, ltspeakergt, etc.
lttitlegt
lt/titlegt
ltspeakergt
lt/speakergt
lt/timegt
lttimegt
lt/locationgt
ltlocationgt
ltabstractgt
lt/abstractgt
ltbiosketchgt
lt/biosketchgt
lthostgt
lt/hostgt
after Frank van Harmelen and Jim Hendler
51
XML ? machine accessible meaning
But, to your machine, the tags still look like
this. The tag names carry no meaning. XML DTDs
and Schemas have little or no semantics.
lttitlegt
lt/titlegt
ltspeakergt
lt/speakergt
lttimegt
lt/timegt
lt/locationgt
ltlocationgt
ltabstractgt
lt/abstractgt
ltbiosketchgt
lt/biosketchgt
lthostgt
lt/hostgt
after Frank van Harmelen and Jim Hendler
52
XML Schema helps
lt?xml version"1.0" encoding"utf-8"?gt
ltxsschema xmlnsxs"http//www.w3.org/2001/XMLSch
ema"gt ltxselement name"book"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"title" type"xsstring"/gt
ltxselement name"author"
type"xsstring"/gt
ltxselement name"character" minOccurs"0"
maxOccurs"unbounded"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"name" type"xsstring"/gt
ltxselement
name"friend-of" type"xsstring" minOccurs"0"

maxOccurs"unbounded"/gt
ltxselement name"since"
type"xsdate"/gt
ltxselement name"qualification"
type"xsstring"/gt
lt/xssequencegt
lt/xscomplexTypegt
lt/xselementgt
lt/xssequencegt
ltxsattribute name"isbn" type"xsstring"/gt
lt/xscomplexTypegt
lt/xselementgt lt/xsschemagt

• XML Schemas provide a simple mechanism to define
  shared vocabularies.

XML Schema file
after Frank van Harmelen and Jim Hendler
53
But there are many schemas
lt?xml version"1.0" encoding"utf-8"?gt
ltxsschema xmlnsxs"http//www.w3.org/2001/XMLSch
ema"gt ltxselement name"book"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"title" type"xsstring"/gt
ltxselement name"author"
type"xsstring"/gt
ltxselement name"character" minOccurs"0"
maxOccurs"unbounded"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"name" type"xsstring"/gt
ltxselement
name"friend-of" type"xsstring" minOccurs"0"

maxOccurs"unbounded"/gt
ltxselement name"since"
type"xsdate"/gt
ltxselement name"qualification"
type"xsstring"/gt
lt/xssequencegt
lt/xscomplexTypegt
lt/xselementgt
lt/xssequencegt
ltxsattribute name"isbn" type"xsstring"/gt
lt/xscomplexTypegt
lt/xselementgt lt/xsschemagt
lt?xml version"1.0" encoding"utf-8"?gt
ltxsschema xmlnsxs"http//www.w3.org/2001/XMLSch
ema"gt ltxselement name"book"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"title" type"xsstring"/gt
ltxselement name"author"
type"xsstring"/gt
ltxselement name"character" minOccurs"0"
maxOccurs"unbounded"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"name" type"xsstring"/gt
ltxselement
name"friend-of" type"xsstring" minOccurs"0"

maxOccurs"unbounded"/gt
ltxselement name"since"
type"xsdate"/gt
ltxselement name"qualification"
type"xsstring"/gt
lt/xssequencegt
lt/xscomplexTypegt
lt/xselementgt
lt/xssequencegt
ltxsattribute name"isbn" type"xsstring"/gt
lt/xscomplexTypegt
lt/xselementgt lt/xsschemagt
XML Schema file 42
XML Schema file 1
after Frank van Harmelen and Jim Hendler
54
Theres no way to relate schema
Either manually or automatically.XML Schema is
weak on semantics.
55
An Ontology level is needed
lt?xml version"1.0" encoding"utf-8"?gt
ltxsschema xmlnsxs"http//www.w3.org/2001/XMLSch
ema"gt ltxselement name"book"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"title" type"xsstring"/gt
ltxselement name"author"
type"xsstring"/gt
ltxselement name"character" minOccurs"0"
maxOccurs"unbounded"gt
ltxscomplexTypegt
ltxssequencegt
ltxselement name"name" type"xsstring"/gt
ltxselement
name"friend-of" type"xsstring" minOccurs"0"

maxOccurs"unbounded"/gt
ltxselement name"since"
type"xsdate"/gt
ltxselement name"qualification"
type"xsstring"/gt
lt/xssequencegt
lt/xscomplexTypegt
lt/xselementgt
lt/xssequencegt
ltxsattribute name"isbn" type"xsstring"/gt
lt/xscomplexTypegt
lt/xselementgt lt/xsschemagt
XMLOntology256

• Ontologies add
• Structure
• Constraints
• mappings

imports
imports

ltgt
We need a way to define ontologies in XMLSo we
can relate themSo machines can understand (to
some degree) their meaning
56
The Semantic Web Wave
57
RDF is the first SW language
Graph
XML Encoding
RDF Data Model
ltrdfRDF ..gt lt.gt lt.gt lt/rdfRDFgt
Good For HumanViewing
Good for MachineProcessing
Triples
stmt(docInst, rdf_type, Document) stmt(personInst,
rdf_type, Person) stmt(inroomInst, rdf_type,
InRoom) stmt(personInst, holding,
docInst) stmt(inroomInst, person, personInst)
RDF is a simple language for building graph based
representations
Good For Reasoning
58
Simple RDF Example
http//umbc.edu/finin/talks/idm02/
dcTitle
Intelligent Information Systemson the Web and
in the Aether
dcCreator
bibAff
bibemail
http//umbc.edu/
bibname
finin_at_umbc.edu
Tim Finin
59
XML encoding for RDF
ltrdfRDF xmlnsrdf"http//www.w3.org/1999/02/22-r
df-syntax-ns" xmlnsdc"http//purl.org/dc/el
ements/1.1/" xmlnsbib"http//daml.umbc.edu/o
ntologies/bib/"gt ltdescription about"http//umbc.e
du/finin/talks/idm02/"gt ltdctitlegtIntelligent
Information Systems on the Web and in the
Aetherlt/dcTitlegt ltdccreatorgt
ltdescriptiongt ltbibNamegtTim
Fininlt/bibNamegt ltbibEmailgtfinin_at_umbc.edult/
bibEmailgt ltbibAff resource"http//umbc.ed
u/" /gt lt/descriptiongt lt/dcCreatorgt lt/descr
iptiongt lt/rdfRDFgt
60
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/

ltfoafPersongt ltfoafnamegtTim Fininlt/foafnamegt ltfo
afmbox_sha1sumgt241037262c252elt/foafmbox_sha1sum
gt ltfoafhomepage rdfresource"http//umbc.edu/fi
nin/" /gt ltfoafimg rdfresource"http//umbc.edu/
finin/images/passport.gif" /gt lt/foafPersongt
61
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 others and know when
  youre talking about the same entities. 

After Dan Brickley, danbri_at_w3.org 
62
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

63
RDFS supports simple inferences
New and Improved! 100 Betterthan XML!!

• 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.

parent a property. person a class. woman subClass
person. mother a property. eve a person a
woman parent cain. cain a person.
_at_prefix rdfs lthttp//www.....gt. _at_prefix
ltgenesis.n3gt. parent rdfsdomain person
rdfsrange person. mother rdfssubProperty
parent rdfsdomain woman eve mother cain.
64
W3Cs Web Ontology Language (OWL)

• DAMLOIL 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) introducesrestrictions
  
• OWL Lite is an entry level languageintended to
  be easy to understandand implement

65
OWL in One Slide

• ltrdfRDF xmlnsrdf "http//w3.org/22-rdf-syntax-n
  s"
• xmlnsrdfshttp//w3.org/rdf-schemagt
  xmlnsowl"http//www.w3.org/2002/07/owlgt
• ltowlOntology rdfabout""gt
• ltowlimports rdfresource"http//owl.org/owl
  oil"/gt
• lt/owlOntologygt
• ltowlClass rdfID"Person"gt
• ltrdfssubClassOf rdfresource"Animal"/gt
• ltrdfssubClassOfgt
• ltowlRestrictiongt
• ltowlonProperty rdfresource"hasParent"/gt
• ltowlallValuesFrom rdfresource"Person"/gt
• lt/owlRestrictiongt
• lt/rdfssubClassOfgt
• ltrdfssubClassOfgt
• ltowlRestriction owlcardinality"1"gt
• ltowlonProperty rdfresource"hasFather"/gt
• lt/owlRestrictiongt
• lt/rdfssubClassOfgt
• lt/owlClassgt

OWL is built on top of XML and RDF
It allows the definition, sharing, composition
and use of ontologies
OWL is a frame based knowledge representation
language
It can be used to add metadata about anything
which has a URI.
URIs are a W3C standard generalizing URLs
everything has a URI
66
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
• Netscapes Mozilla web browser, open directory
  (http//dmoz.org/)
• Adobe products via XMP (eXtensible Metadata
  Platform)
• Web communities LiveJournal, Ecademy, and
  Cocolog
• In Microsofts VISTA Connected Services
  Framework uses an RDF database and SPARQL
• Oracles 10g and 11g products
• Yahoos food portal
• Joost TV over the web startup

67
SPARQL Example

• BASE lthttp//example.org/gt
• PREFIX rdf lthttp//www.w3.org/1999/02/22-rdf-synt
  ax-nsgt
• PREFIX foaf lthttp//xmlns.com/foaf/0.1/gt
• PREFIX ex ltproperties/1.0gt
• SELECT DISTINCT person ?name age
• FROM lthttp//rdf.example.org/people.rdfgt
• WHERE person a foafPerson
• foafname ?name.
• OPTIONAL person exage age
  .
• FILTER ! REGEX(?name, "Bob")
• LIMIT 3 ORDER BY ASC?name

68
Some applications involving ACLs and the
Semantic Web
69
ITTALKS Architecture
Web server Java servlets
Web Services
People
MapBlast, CiteSeer,Google,
HTTP
HTTP, WebScraping
Email, HTML, SMS, WAP
ApacheTomcat
Agents
FIPA ACL, KQML, DAML
SQL
RDBMS
DB
HTTP, KQML, DAML, Prolog
DAMLreasoningengine
Databases
DAML files
70
TAGA
Travel Agent Game in Agentcities

• Technologies
• FIPA (JADE, April Agent Platform)
• Semantic Web (RDF, OWL)
• Web (SOAP,WSDL,DAML-S)
• Internet (Java Web Start )

• Features
• Open Market Framework
• Auction Services
• OWL message content
• OWL Ontologies
• Global Agent Community

• Motivation
• Market dynamics
• Auction theory (TAC)
• Semantic web
• Agent collaboration (FIPA Agentcities)

• 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
http//taga.umbc.edu/
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
71
http//ebiquity.umbc.edu/

• Our research groups 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.

72
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.htmVideo
73
Fujitsu Task Computing
http//www.taskcomputing.org/

• Objective Make computing available throughout
  the physical environment while it is effectively
  invisible to the users

Play Jeffs Video Dial Contact from
Outlook Weather Info of FLA, CP
OS/Application
e-Services
Device
Video from DV
Video from DV
Add into Outlook
Dial
Open
Save
Print
Add into Outlook
Dial
Open
Save
Print
Aerial Photo of
Weather Info of
Aerial Photo of
Weather Info of
Jeffs Video
Play (Video)
Play (Audio)
View
Contact from Outlook
Jeffs Video
Play (Video)
Play (Audio)
View
Contact from Outlook
OS/Application
Devices
Web Pages
74
The Context Broker Architecture
http//cobra.umbc.edu/
Access to more information
Knowledge sharing
Policy
75
The EasyMeeting System
76
An EasyMeeting Scenario
77
An EasyMeeting Scenario
78
The SOUPA Ontology
79
2010-and Beyond
80

• It's hard to make predictions, especially about
  the future

81
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

82
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83
Conclusions
84
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.