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Related papers: The Attack as Strong Negation, Part I

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We show that an interesting class of feed-forward neural networks can be understood as quantitative argumentation frameworks. This connection creates a bridge between research in Formal Argumentation and Machine Learning. We generalize the…

Neural and Evolutionary Computing · Computer Science 2020-12-11 Nico Potyka

Building an effective adversarial attacker and elaborating on countermeasures for adversarial attacks for natural language processing (NLP) have attracted a lot of research in recent years. However, most of the existing approaches focus on…

Computation and Language · Computer Science 2020-10-20 Wenjuan Han , Liwen Zhang , Yong Jiang , Kewei Tu

We look at non-classical negations and their corresponding adjustment connectives from a modal viewpoint, over complete distributive lattices, and apply a very general mechanism in order to offer adequate analytic proof systems to logics…

Logic in Computer Science · Computer Science 2016-06-24 Ori Lahav , João Marcos , Yoni Zohar

We introduce a refutation graph calculus for classical first-order predicate logic, which is an extension of previous ones for binary relations. One reduces logical consequence to establishing that a constructed graph has empty extension,…

Logic in Computer Science · Computer Science 2013-04-01 Paulo A. S. Veloso , Sheila R. M. Veloso

Hundreds of defenses have been proposed to make deep neural networks robust against minimal (adversarial) input perturbations. However, only a handful of these defenses held up their claims because correctly evaluating robustness is…

Machine Learning · Computer Science 2022-06-29 Roland S. Zimmermann , Wieland Brendel , Florian Tramer , Nicholas Carlini

Adversarial attacks are usually expressed in terms of a gradient-based operation on the input data and model, this results in heavy computations every time an attack is generated. In this work, we solidify the idea of representing…

Machine Learning · Computer Science 2023-08-01 Rajdeep Haldar , Qifan Song

Finding attackable sentences in an argument is the first step toward successful refutation in argumentation. We present a first large-scale analysis of sentence attackability in online arguments. We analyze driving reasons for attacks in…

Computation and Language · Computer Science 2020-10-07 Yohan Jo , Seojin Bang , Emaad Manzoor , Eduard Hovy , Chris Reed

Classical adversarial attacks are phrased as a constrained optimisation problem. Despite the efficacy of a constrained optimisation approach to adversarial attacks, one cannot trace how an adversarial point was generated. In this work, we…

Machine Learning · Computer Science 2025-03-18 Lachlan Simpson , Federico Costanza , Kyle Millar , Adriel Cheng , Cheng-Chew Lim , Hong Gunn Chew

In this chapter, we introduce a new dialogical system for first order classical logic which is close to natural language argumentation, and we prove its completeness with respect to usual classical validity. We combine our dialogical system…

Computation and Language · Computer Science 2020-08-18 Davide Catta , Richard Moot , Christian Retoré

Value-based argumentation enhances a classical abstract argumentation graph - in which arguments are modelled as nodes connected by directed arrows called attacks - with labels on arguments, called values, and an ordering on values, called…

Multiagent Systems · Computer Science 2019-07-23 Grzegorz Lisowski , Sylvie Doutre , Umberto Grandi

We propose a new formalism for specifying and reasoning about problems that involve heterogeneous "pieces of information" -- large collections of data, decision procedures of any kind and complexity and connections between them. The essence…

Logic in Computer Science · Computer Science 2016-12-30 Eugenia Ternovska

There has been an ongoing cycle where stronger defenses against adversarial attacks are subsequently broken by a more advanced defense-aware attack. We present a new approach towards ending this cycle where we "deflect'' adversarial attacks…

Machine Learning · Computer Science 2020-02-19 Yao Qin , Nicholas Frosst , Colin Raffel , Garrison Cottrell , Geoffrey Hinton

We study instantiated abstract argumentation frames of the form $(S,R,I)$, where $(S,R)$ is an abstract argumentation frame and where the arguments $x$ of $S$ are instantiated by $I(x)$ as well formed formulas of a well known logic, for…

Artificial Intelligence · Computer Science 2015-04-28 D. M. Gabbay

The goal of this paper is to extend classical logic with a generalized notion of inductive definition supporting positive and negative induction, to investigate the properties of this logic, its relationships to other logics in the area of…

Logic in Computer Science · Computer Science 2009-09-25 Marc Denecker

In this paper, we present a preliminary work on an approach to fill the gap between logic-based argumentation and the numerous approaches to tackle the dynamics of abstract argumentation frameworks. Our idea is that, even when arguments and…

Artificial Intelligence · Computer Science 2016-03-30 Jean-Guy Mailly

In Dung's abstract argumentation, arguments are either acceptable or unacceptable, given a chosen notion of acceptability. This gives a coarse way to compare arguments. In this paper, we propose a counting approach for a more fine-gained…

Artificial Intelligence · Computer Science 2015-07-21 Fuan Pu , Jian Luo , Yulai Zhang , Guiming Luo

Non-classical negations may fail to be contradictory-forming operators in more than one way, and they often fail also to respect fundamental meta-logical properties such as the replacement property. Such drawbacks are witnessed by intricate…

Logic in Computer Science · Computer Science 2017-07-26 Ori Lahav , João Marcos , Yoni Zohar

This literature review discovers an implementation of formal logic systems in cyber security by enhancing access control models. We explore the characteristics of the existing access control theories, their limitations and how classical…

Logic in Computer Science · Computer Science 2023-08-28 Alvin Tang

Recent works have empirically shown that there exist adversarial examples that can be hidden from neural network interpretability (namely, making network interpretation maps visually similar), or interpretability is itself susceptible to…

Machine Learning · Computer Science 2020-10-23 Akhilan Boopathy , Sijia Liu , Gaoyuan Zhang , Cynthia Liu , Pin-Yu Chen , Shiyu Chang , Luca Daniel

This paper defines an argumentation semantics for extended logic programming and shows its equivalence to the well-founded semantics with explicit negation. We set up a general framework in which we extensively compare this semantics to…

Logic in Computer Science · Computer Science 2007-05-23 Ralf Schweimeier , Michael Schroeder