2,067 research outputs found
Special issue on logics and artificial intelligence
There is a significant range of ongoing challenges in artificial intelligence (AI) dealing with reasoning, planning, learning, perception and cognition, among others. In this scenario, many-valued logics emerge as one of the topics in many of the solutions to some of those AI problems. This special issue presents a brief introduction to the relation between logics and AI and collects recent research works on logic-based approaches in AI
Probabilistic interpretations of argumentative attacks: logical and experimental foundations
We present an interdisciplinary approach to study systematic relations between logical form and attacks between claims in an argumentative framework. We propose to generalize qualitative attack principles by quantitative ones. Specifically, we use coherent conditional probabilities to evaluate the rationality of principles which govern the strength of argumentative attacks. Finally, we present an experiment which explores the psychological plausibility of selected attack principles
Semi-Abstract Value-Based Argumentation Framework
In his seminal paper, Phan Minh Dung (1995) proposed abstract argumentation
framework, which models argumentation using directed graphs where structureless
arguments are the nodes and attacks among the arguments are the edges. In the
following years, many extensions of this framework were introduced. These
extensions typically add a certain form of structure to the arguments. This
thesis showcases two such extensions -- value-based argumentation framework by
Trevor Bench-Capon (2002) and semi-abstract argumentation framework by Esther
Anna Corsi and Christian Ferm\"uller (2017). The former introduces a mapping
function that links individual arguments to a set of ordered values, enabling a
distinction between objectively and subjectively acceptable arguments. The
latter links claims of individual arguments to propositional formulae and then
applies newly-introduced attack principles in order to make implicit attacks
explicit and to enable a definition of a consequence relation that relies on
neither the truth values nor the interpretations in the usual sense.
The contribution of this thesis is two-fold. Firstly, the new semi-abstract
value-based argumentation framework is introduced. This framework maps
propositional formulae associated with individual arguments to a set of ordered
values. Secondly, a complex moral dilemma is formulated using the original and
the value-based argumentation frameworks showcasing the expressivity of these
formalisms.Comment: Submitted as a Bachelor Thesis at TU Wien on 2019-11-07. Advisor:
Christian Ferm\"uller. 49 page
Nije ni potrebno govoriti o tome (iako Äu svejedno reÄi)
It is not very frequently assumed that negation may play an active role in achieving specific conceptual frames, but as claimed by Langacker (2008) or Lakoff (2004), language enables the actual physical presence of words, even if in some kind of a negative construction, to create the positive conception of what is being denied.
Our research focuses on the phenomenon of praeteritio or apophasis as a rhetorical device in political discourse, where we noticed a frequent use of various types of negation constructions as introductory lines for the content which is actually not being negated but rather accentuated. Structures like āIt goes without sayingā¦ā, āWe donāt want to mention thatā¦ā, etc., which are then followed by actual descriptions of affected participants or events, have been spotted in our corpus of public political speech events, particularly in the media discourse and in other types of discourse involved in shaping public opinion.
The cognitive and pragmatic functions of apophatic structures in the elicited corpus are analysed as well as their role in creating the persuasive force of this rhetorical device. Their iconic nature and psycholinguistic background are used as a vehicle to explain their unique position in the process of conceptualization of the world around us.Ne smatra se Äesto da negacija može imati aktivnu ulogu u postizanju odreÄenih konceptualnih okvira, no kao Å”to tvrde Langacker (2008) ili Lakoff (2004), jezik omoguÄava stvarnoj fiziÄkoj prisutnosti rijeÄi, Äak i ako se one nalaze u nekoj vrsti nijeÄne konstrukcije, stvoriti pozitivnu sliku onoga Å”to se nijeÄe.
NaÅ”e se istraživanje prije svega bavi pretericijom i apofazom kao retoriÄkim sredstvima u politiÄkom diskursu, gdje smo zamijetili Äestu uporabu razliÄitih vrsta nijeÄnih konstrukcija koje uvode sadržaj koji se zapravo ne nijeÄe, veÄ naglaÅ”ava. Konstrukcije poput āNije ni potrebno govoriti...ā, āDa i ne spominjemo...ā, itd. iza kojih neposredno slijedi opis āpreÅ”uÄenihā sudionika ili dogaÄaja, pojavljuju se u naÅ”em korpusu javnih politiÄkih govora, u medijskom diskursu te u drugim tipovima diskursa kojima se oblikuje javno mnijenje.
U radu se analiziraju kognitivne i pragmatiÄke funkcije apofaznih konstrukcija u navedenom korpusu te njihova uloga u stvaranju uvjerljivosti ovoga retoriÄkog sredstva. Njihova ikoniÄka priroda i psiholingvistiÄka pozadina koriste se kao alat za tumaÄenje njihova jedinstvenog položaja u procesu konceptualizacije svijeta oko nas
Evolution of security engineering artifacts: a state of the art survey
Security is an important quality aspect of modern open software systems. However, it is challenging to keep such systems secure because of evolution. Security evolution can only be managed adequately if it is considered for all artifacts throughout the software development lifecycle. This article provides state of the art on the evolution of security engineering artifacts. The article covers the state of the art on evolution of security requirements, security architectures, secure code, security tests, security models, and security risks as well as security monitoring. For each of these artifacts the authors give an overview of evolution and security aspects and discuss the state of the art on its security evolution in detail. Based on this comprehensive survey, they summarize key issues and discuss directions of future research
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A neural cognitive model of argumentation with application to legal inference and decision making
Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data)
Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI 2020)
1st Doctoral Consortium at the European Conference on
Artificial Intelligence (DC-ECAI 2020), 29-30 August, 2020
Santiago de Compostela, SpainThe DC-ECAI 2020 provides a unique opportunity for PhD students, who are close to finishing their doctorate research, to interact with experienced researchers in the field. Senior members of the community are assigned as mentors for each group of students based on the studentās research or similarity of research interests. The DC-ECAI 2020, which is held virtually this year, allows students from all over the world to present their research and discuss their ongoing research and career plans with their mentor, to do networking with other participants, and to receive training and mentoring about career planning and career option
Online Handbook of Argumentation for AI: Volume 1
This volume contains revised versions of the papers selected for the first
volume of the Online Handbook of Argumentation for AI (OHAAI). Previously,
formal theories of argument and argument interaction have been proposed and
studied, and this has led to the more recent study of computational models of
argument. Argumentation, as a field within artificial intelligence (AI), is
highly relevant for researchers interested in symbolic representations of
knowledge and defeasible reasoning. The purpose of this handbook is to provide
an open access and curated anthology for the argumentation research community.
OHAAI is designed to serve as a research hub to keep track of the latest and
upcoming PhD-driven research on the theory and application of argumentation in
all areas related to AI.Comment: editor: Federico Castagna and Francesca Mosca and Jack Mumford and
Stefan Sarkadi and Andreas Xydi
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