Termin

Titel:
Vortrag Andreas Niskanen

Datum / Uhrzeit:
13.06.19   /  15:30 - 16:30

Ort:
25.12.02 Raum 33


Beschreibung:

Einladung des Lehrstuhls "Komplexitätstheorie und Kryptologie" zu einem

Vortrag mit dem Thema

Synthesizing Argumentation Frameworks from Examples

von Herrn Andreas Niskanen (University of Helsinki, Prof. Matti J. Järvisalo)

Abstract:

Argumentation is today a topical area of artificial intelligence (AI) research. Abstract argumentation, with argumentation frameworks (AFs) as the underlying knowledge representation formalism, is a central viewpoint to argumentation in AI. Indeed, from the perspective of AI and computer science, understanding computational and representational aspects of AFs is key in the study of argumentation.

Realizability of AFs has been recently proposed as a central notion for analyzing the expressive power of AFs under different semantics. In this work, we propose and study the AF synthesis problem as a natural extension of realizability, addressing some of the shortcomings arising from the relatively stringent definition of realizability. In particular, realizability gives means of establishing exact conditions on when a given collection of subsets of arguments has an AF with exactly the given collection as its set of extensions under a specific argumentation semantics. However, in various settings within the study of dynamics of argumentation—including revision and aggregation of AFs—nonrealizability can naturally occur. To accommodate such settings, our notion of AF synthesis seeks to construct, or synthesize, AFs that are semantically closest to the knowledge at hand even when no AFs exactly representing the knowledge exist. Going beyond defining the AF synthesis problem, we study both theoretical and practical aspects of the problem. In particular, we (i) prove NP-completeness of AF synthesis under several semantics, (ii) study basic properties of the problem in relation to realizability, (iii) develop algorithmic solutions to NP-hard AF synthesis using the constraint optimization paradigms of maximum satisfiability and answer set programming, (iv) empirically evaluate our algorithms on different forms of AF synthesis instances, as well as (v) discuss variants and generalizations of AF synthesis.

This is joint work with Matti J. Järvisalo from the University of Helsinki and Johannes P. Wallner from TU Wien.  A preliminary version of this work was presented at ECAI 2016, and we just got a journal version - which is currently under minor revisions - accepted to JAIR.


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