Explaining random forests using bipolar argumentation and Markov networks
Random forests are decision tree ensembles that can be used to solve a variety of machine
learning problems. However, as the number of trees and their individual size can be large …
learning problems. However, as the number of trees and their individual size can be large …
[PDF][PDF] Determining the Acceptability of Abstract Arguments with Graph Convolutional Networks.
This paper presents a new deep learning approach to sceptical and credulous acceptance
of arguments, two key problems in Abstract Argumentation that are most commonly solved …
of arguments, two key problems in Abstract Argumentation that are most commonly solved …
[PDF][PDF] An Efficient Algorithm for Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks.
An Efficient Algorithm for Skeptical Preferred Acceptance in Dynamic Argumentation
Frameworks Page 1 Introduction Incremental Computation Experiments Conclusions and future …
Frameworks Page 1 Introduction Incremental Computation Experiments Conclusions and future …
[PDF][PDF] Quantitative Reasoning and Structural Complexity for Claim-Centric Argumentation.
Abstract Argumentation is a well-established formalism for nonmonotonic reasoning and a
vibrant area of research in AI. Claim-augmented argumentation frameworks (CAFs) have …
vibrant area of research in AI. Claim-augmented argumentation frameworks (CAFs) have …
Algorithms for dynamic argumentation frameworks: An incremental SAT-based approach
Motivated by the fact that argumentation is intrinsically a dynamic process, the study of
representational and computational aspects of dynamics in argumentation is starting to gain …
representational and computational aspects of dynamics in argumentation is starting to gain …
On the impact of data selection when applying machine learning in abstract argumentation
We examine the impact of both training and test data selection in machine learning
applications for abstract argumentation, in terms of prediction accuracy and generalizability …
applications for abstract argumentation, in terms of prediction accuracy and generalizability …
[PDF][PDF] Decomposition-Guided Reductions for Argumentation and Treewidth.
Abstract Argumentation is a widely applied framework for modeling and evaluating
arguments and its reasoning with various applications. Popular frameworks are abstract …
arguments and its reasoning with various applications. Popular frameworks are abstract …
[PDF][PDF] Graph Neural Networks for Algorithm Selection in Abstract Argumentation.
We address the task of selecting the fastest algorithm, in terms of runtime, for determining
skeptical acceptance under preferred semantics in abstract argumentation frameworks out of …
skeptical acceptance under preferred semantics in abstract argumentation frameworks out of …
Abstract argumentation with markov networks
We explain how abstract argumentation problems can be encoded as Markov networks.
From a computational perspective, this allows reducing argumentation tasks like finding …
From a computational perspective, this allows reducing argumentation tasks like finding …
[HTML][HTML] Approximating problems in abstract argumentation with graph convolutional networks
In this article, we present a novel approximation approach for abstract argumentation using
a customized Graph Convolutional Network (GCN) architecture and a tailored training …
a customized Graph Convolutional Network (GCN) architecture and a tailored training …