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Using RDF in Agent-Mediated Knowledge Architectures

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Using RDF in Agent-Mediated Knowledge Architectures K. Hui, S. Chalmers, P.M.D. Gray & A.D. Preece University of Aberdeen U.K http://www.csd.abdn.ac.uk/. – PowerPoint PPT presentation

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Title: Using RDF in Agent-Mediated Knowledge Architectures


1
Using RDF in Agent-Mediated Knowledge
Architectures
K. Hui, S. Chalmers, P.M.D. Gray A.D. Preece
University of Aberdeen U.K http//www.csd.abdn.ac.
uk/. Part of AKT(Advanced Knowledge
Technology) Consortium supported by EPSRC
2
Outline
  • RDFS - Schema for Semantic Web
  • - Metaschema extended to hold FOL Constraints
  • Use of RDF in AM Knowledge Architectures
  • KRAFT information integration fusion
  • CONOISE virtual organisations with Autonomy
    subject to Constraints
  • Conclusions

3
What we believe
  • Representing knowledge make sense only if it is
    used in reasoning by machines
  • More direct use of RDF in knowledge architectures
  • RDFS makes RDF usable within a semantic data
    model as in Edutella (Risch et al)
  • extra semantic layers can be built above RDF
    using built-in extensibility of RDFS
  • Agent langs should use RDF(S) for content

4
Pros Cons of RDF
  • Pros
  • Tree -gt DAG
  • XML Serialisn
  • Extensible by RDFS
  • stable
  • cross-platform
  • good Java support (Jena parser, FrodoViz)
  • uniform representation (data meta-data)
  • Cons
  • Simple
  • lack of DL expressiveness
  • wordy (for humans)

5
RDF(S) Triple Representation
  • RDF triples
  • subject-predicate-object
  • Jena tool creates as Java objects
  • We can map triples to Prolog terms
  • almost canonical form
  • easy to add on extra triples (easier than graph
    arcs)

Applications
RDF
triples
Prolog terms
Java objects
6
Case Study 1 - Capturing Knowledge in KRAFT
  • Fuses mobile constraints for Configuration
    problem
  • CSP solving by Sicstus/Eclipse solver
  • Knowledge to capture
  • domain model (schema)
  • data instances
  • choices (solution space results)
  • quantified constraints (CoLan/CIF)
  • requirement, restrictions

7
Capturing Data Instances Domain Model
  • Domain Model
  • map P/FDM schema into RDFS
  • web-enabling the schema
  • losing some knowledge
  • e.g. cardinality, key
  • can be added to metadata layers (cifentmet)
  • Data Instances
  • make use of domain model defined in RDFS

8
Domain Model Example
ltrdfsClass rdfID"pc"gt ltrdfssubClassOf
rdfresource "http//www.w3.org/2000/01/rdf-s
chema Resource"/gt lt/rdfsClassgt ltrdfsCl
ass rdfID"os"gt ltrdfssubClassOf
rdfresource "http//www.w3.org/2000/01/rdf-s
chema Resource"/gt lt/rdfsClassgt ltrdfPro
perty rdfID"has_os"gt ltrdfsdomain
rdfresource"pc"/gt ltrdfsrange
rdfresource"os"/gt lt/rdfPropertygt
declare os -gtgt entity ... declare pc -gtgt
entity declare memory(pc) -gt integer declare
has_os(pc) -gt os ...
9
Constraint Examples in CoLan
constrain each p in pc to have
size(has_os(p)) lt size(has_disk(p)) constrain
each p in pc some s in slots(pc) has
sltype(s)USB constrain each t in tutor such
that astatus(t) research each st in
advisees(t) has grade(st) gt 60
10
Constraints in RDF
  • Constraint language definition in RDFS
  • a richer semantics cleanly layered on top of RDF
  • contains classes of meta-objects (e.g.
    cifentmet, cifpropmet) like meta-relns for
    relational DB
  • other metaclasses capture parse tree of
    Constraint
  • Advantages
  • a clear layering, no change of RDF(S)
  • constraint become self-contained
  • URI cross-ref to domain model (in RDFS)
  • constraints become resources

11
Constraints in RDF
RDF Schema of the PC config domain
RDF Schema of domain X
RDF Schema of the CIF language
RDFS
constraint on domain X in RDF
constraint on the PC config domain in RDF
RDF
12
Constraint Example in RDF
ltrdfRDF ... xmlnscif"http//www.csd.abdn.ac.uk/
khui/akt/cif/cif-rdfs.xml"gt
ltcifimpliesconstr rdfID"eg1"gt ltcifqvargt
ltcifsetmemgt ltcifsetmem_vargt
ltcifvariable rdfID"uevar1"gt
ltcifvarnamegtuevar1lt/cifvarnamegt
lt/cifvariablegt lt/cifsetmem_vargt
ltcifsetmem_setgt ltcifentsetgt
ltcifentset_entclassgt ltcifentmet
rdfID"entmet_pc"gt
ltcifentmet_rdfnamegthttp//www.csd.abdn.ac.uk/sch
almer/schema/pc_schemapc
lt/cifentmet_rdfnamegt
lt/cifentmetgt lt/cifentset_entclassgt
lt/cifentsetgt lt/cifsetmem_setgt
lt/cifsetmemgt lt/cifqvargt ...
13
Knowledge-directed Mapping
mapping engine
14
Using RDF-Encoded Knowledge (Continued)
  • Domain-aware constraint fusion
  • constraint inheritance
  • a constraint that applies to objects of a class
    also applies to objects of its subclasses
  • need knowledge on the class hierarchy
  • an RDF constraint contains pointers to its domain
    model in RDFS
  • look for rdfssubClassOf triples

15
Case Study 2 - Conoise
  • formation of virtual organisations by autonomous
    agents
  • based on the BDI model
  • desires represented as constraints (CIF/RDF)
  • agents built using JADE
  • content language in CIF/RDF
  • use Jena to parse manipulate CIF/RDF
  • store queried as Java objects

16
BDI Agents using RDF knowledge
  • A CONOISE agent has to combine knowledge from
    different sources. RDF(S) provides a common basis
    for doing this.
  • It exercises its Autonomy by planning Intentions
    in order to meet its various Desires acquired
    from different sources as (RDFS Constraints) .
  • It resolves conflicting desires through a
    Constraint Solver.
  • The Solvers domain knowledge is held as Beliefs
    read in as RDF facts.

17
Conclusions
  • FOL Constraints,
  • referring to Data items defined in an RDFS
    Ontology,
  • can themselves be captured in RDFS
  • FIPA Agent langs should use RDF(S) for content
  • stability (W3C standard and XML serialisn)
  • portability (esp. through Java)
  • capability to store DAG of various object types
  • rich contentdomain modelinstancesFOL
    constraints
  • extensibility by building extra layer(s) on top
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