DARPA Agent Markup Language

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DARPA Agent Markup Language

• Ashish Jain
• University of Colorado at Boulder

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What is DAML ?

• Technology to enable software agents to
  dynamically identify and understand information
  sources.
• Formatting web so that it can easily be
  understood by intelligent agents
• Express ontologies (formal specification of a
  concept vocabularies , inter-relationships etc)
  
• Add reasoning cues
• Disjoint from , union of , transitive

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DAML Status

• Currently being explored at University level
• SHOE (Maryland) , OWL (Washington)
• Largely grows from past DARPA projects
• But not transitioning
• W3C focused on short-term gains HTML/XML

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DAML Objectives

• Create an Agent Mark-Up Language (DAML) built
  upon XML that allows users to provide
  machine-readable semantic annotations for
  specific communities of interest.
• Create tools that embed DAML markup on to web
  pages and other information sources in a manner
  that is transparent and beneficial to the users.
  
• Use these tools to build up, instantiate,
  operate, and test sets of agent-based programs
  that markup and use DAML

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DAML vs HTML vs XML vs RDF

• HTML
• Limited set of tags , not suitable for search
• XML
• Extensible tags
• Useful for data sharing
• but still not good for searching
• RDF
• We can only define global range on properties (
  i.e. for all classes ? apply constraints)
• No mechanism for providing necessary and
  sufficient conditions
• No support transitivity

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DAML Example

• Find information about a researcher named James
  Hendler
• Find a reference to a paper about SHOE coauthored
  by James Handler
• Find a reference to the most recent paper about
  SHOE coauthored by James Handler

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Query Processing (I)

• DAML ontologies for publication, researchers and
  topic have been built.
• First query can be formalized as

ltXmlns SRIRes http//ai.src.com/daml/ontologie
s/Reseachersgt ltSRIRes Reseachergt ltfirstnamegtJame
slt/firstnamegt ltlastnamegtHendlerlt/lastnamegt lttitlegt
Dr.lt/titlegt lt/SRIResReseachergt
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Query Processing (II)

• After parsing the query , it is passed to DAML-Q
  ( DAML query engine)
• Looks for the namespace identifier, and
  sequentially searches the content of the web
  pages.
• Could be complicated because of presence of
  indirect ontological reference.

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Inference in Queries (I)

• Uses first order theorem prover such as SNARK
• Written in LISP

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Inference in Queries (II)

• Third query can be formalized as

(find) ?paperq such-that (and
(pub-val ?paperq ?paper (author ?paper
?person (person-val (personq James Hendler
) ?person ) (about paper (paperq SHOE))
( (pub-to-year ?paper) (year-fn
?natural))) prefer starts-after-starting-of on
(year-fn ?natural) Time-limit 10)
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Conclusions (I)

• Allows semantic interoperability at the level we
  currently have syntactic interoperability in XML
• Revolutionizing web interoperability
• Objects in the web can be marked (manually or
  automatically) to include the following
• Description of data they contain
• Description of function they provide
• Description of data they provide
• This marks the environment for agents

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Conclusion (II)

• Lack of user tools to create it
• Lack of agents that understand it
• But step in right direction