we are pleased to announce a tutorial about "Probabilistic
Argumentation Systems" held at the IJCAI'99 conference in Stockholm.
Note that the tutorial will take place on Sunday, August 1, 1999,
2pm-6pm. It can therefore be combined with the preceding UAI'99
conference. For more information about the IJCAI and the UAI
conferences (program, registration, etc.) we refer to=20
http://www.dsv.su.se/ijcai-99/ and http://uai99.iet.com/.
The theory of "Probabilistic Argumentation Systems" is a promising
approach for non-monotonic reasoning under uncertainty. It allows to
judge open questions (hypotheses) about the unknown or future world in
the light of the given uncertain knowledge. The theory is based on a
novel combination of probability theory and classical logic. It handles
the case of total ignorance properly, and there is no restriction to
DAGs like in Bayesian inference. See below for a more precise tutorial
description.
Thanks for your interest and best wishes,
Rolf Haenni & Juerg Kohlas
University of Fribourg, Switzerland
http://www2-iiuf.unifr.ch/tcs/
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TUTORIAL DESCRIPTION
Probabilistic argumentation systems provide an intuitive and natural
approach to non-monotonic reasoning under uncertainty. The basic idea
is to find arguments in favor and against certain hypotheses. Arguments
are composed of uncertain assumptions, which are used for capturing the
uncertainty of the given knowledge. Deriving arguments is a matter of
deduction in an appropriate logic. Non-monotonicity is obtained in a
natural way by eliminating contradictory arguments.
A quantitative judgement of hypotheses is possible by weighing the
uncertain assumptions according to their likelihood or probability. In
this way, reliabilities of arguments are obtained and degrees of
support and plausibility in the sense of the Dempster-Shafer theory of
evidence can be derived for the hypotheses. Probabilistic argumentation
systems are therefore based on a novel combination of classical logic
(for deduction) and probability theory (for measuring the reliabilities
of deductions). The tutorial will present the conceptual foundations of
probabilistic argumentation systems. Furthermore, relations to other
formalism (e.g. Bayesian networks, evidence theory, ATMS, probabilistic
logic, default logic, etc.) will be elucidated.
The expressiveness of probabilistic argumentation systems permits to
model problems from different domains (e.g. model-based prediction,
state estimation and diagnostics, failure trees, project scheduling,
sensor fusing, testimonies, public key certification, information
retrieval, etc.). This shows its extensive applicability and usefulness
for all sorts of problems of reasoning under uncertainty. Several
examples of different application fields will be discussed in the
tutorial.
Efficient deduction mechanisms are of particular importance for
probabilistic argumentation systems. For that purpose, appropriate
approximation strategies exist for computing only the most relevant
arguments in polynomial time. In this way, the complexity of dealing
with logical deduction can be controlled. Based on these
considerations, inference mechanisms for probabilistic argumentation
systems will be sketched.=20
PREREQUISITE KNOWLEDGE
Only elementary knowledge of propositional logic and discrete
probability is required.=20
INFORMATION ABOUT THE LECTURERS
Both lecturers are experienced in the tutorial topic for many years:
- Prof. J=FCrg Kohlas is professor for theoretical computer science at
the University of Fribourg (Switzerland). He has been a partner of the
European Basic Research Activity "Defeasible Reasoning and Management
of Uncertainty" (1993-1996). He is the leader of the project
"Probabilistic Argumentation Systems" (1997-1999) and the initiator of
the project "Inference and Deduction: an Integration of Logic and
Probability", both sponsored by the Swiss National Foundation for
Research.
- Dr. Rolf Haenni is research scientist at the Institute of Informatics
of the University of Fribourg. He has been a partner of the European
Basic Research Activity "Defeasible Reasoning and Management of
Uncertainty" (1993-1996), and he is the manager of the project
"Probabilistic Argumentation Systems" (1997-1999).
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* Institute of Informatics (IIUF) __/ __/ __/ __/ __/ =20
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* University of Fribourg, Switzerland __/ __/ __/ __/ _____/ =20
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* Email: rolf.haenni@unifr.ch __/ __/ ______/ __/ =20
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