Download DARPA Agent Markup Language

DARPA Agent Markup Language
Ashish Jain
University of Colorado at Boulder
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
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
DAML: Objectives
1.
Create an Agent Mark-Up Language (DAML)
built upon XML that allows users to provide
machine-readable semantic annotations for
specific communities of interest.
2.
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.
3.
Use these tools to build up, instantiate, operate,
and test sets of agent-based programs that
markup and use DAML
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
DAML: Example
1.
Find information about a researcher
named James Hendler
2.
Find a reference to a paper about SHOE
coauthored by James Handler
3.
Find a reference to the most recent
paper about SHOE coauthored by James
Handler
Query Processing (I)

DAML ontologies for publication,
researchers and topic have been built.

First query can be formalized as :
<Xmlns: SRIRes =
http://ai.src.com/daml/ontologies/Reseachers#>
<SRIRes: Reseacher>
<firstname>James</firstname>
<lastname>Hendler</lastname>
<title>Dr.</title> </SRIRes:Reseacher>
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.
Inference in Queries (I)

Uses first order theorem prover such as
SNARK

Written in LISP
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)
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
Conclusion (II)

Lack of user tools to create it

Lack of agents that understand it

But step in right direction