Program, INAP2001, Oct 20-22, 2001
The University of Tokyo, Sanjo Conference Hall, Japan
| Streams |
| Content Management |
| Sessions |
| Tutorial |
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| Decision Support |
| Sessions |
| Invited Talk | |
| Donald Nute | |
Making decisions with incomplete information: |
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| Speaker: |
Donald Nute http://ai.uga.edu/~dnute Department of Philosophy, Artificial Intelligence Center, The University of Georgia, USA http://www.ai.uga.edu |
| Abstract: |
We often reach conclusions partially on the basis that we do not have evidence that
the conclusion is false. A newspaper story warning that the local water supply has
been contaminated would prevent a person from drinking water from the tap in her
home. This suggests that the absence of such evidence contributes to her usual belief
that her water is safe. On the other hand, if a reasonable person received a letter
telling her that she had won a million dollars, she would consciously consider
whether there was any evidence that the letter was a hoax or somehow misleading
before making plans to spend the money. All to often we arrive at conclusions which
we later retract when contrary evidence becomes available. The contrary evidence
_defeats_ our earlier reasoning. Much of our reasoning is _defeasible_ in this way.
Since around 1980, considerable research in AI has focused on how to model reasoning
of this sort. In this talk, I will consider one theoretical approach to this problem,
discuss implementation of this approach as an extension of logic programming
(Prolog,) and describe some application of this work to legal reasoning, learning,
planning, and other types of automated reasoning.
|
| Invited Talk | |
| Harold Boley | |
The Rule Markup Language: |
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| Speaker: |
Harold Boley http://www.dfki.uni-kl.de/~boley German Research Center for Artificial Intelligence, Germany http://www.dfki.de |
| Abstract: | Shared declarative aspects of Prolog and XML are examined. An XML version of pure Prolog is shown to be at the center of the Rule Markup Language http://www.dfki.de/ruleml. The RuleML Data Model uses order-labeled trees, combining the RDF and XML models. As part of RuleML's hierarchy of sublanguages, the RuleML-Prolog DTD is developed into an XML Schema. XSLT (XSL Transformations) is employed for practical XML-to-XML and XML-to-XHTML transformation of Prolog on the Web. |
| Networking |
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The organizers reserve the right the change the program.