Weakly-admissible Semantics and the Propagation of Ambiguity in Abstract Argumentation Semantics

The concept of ambiguous literals of defeasible logics is mapped to the set of undecided arguments identified by an argumentation semantics. It follows that Dung’s complete semantics are all ambiguity propagating, since the undecided status of an attacking argument is always propagated to the attacked argument, unless the latter is defeated by another accepted argument. In this paper we investigate a novel family of abstract argumentation semantics, called weakly-admissible semantics, where we do not require an acceptable argument to be necessarily defended from the attacks of undecided arguments. Weakly-admissible semantics are conflict-free, ambiguity blocking, non-admissible (in Dung’s sense), but employing a more relaxed defence-based notion of admissibility; they allow reinstatement and generate extensions that are super-sets of grounded semantics, and they at least accept credulously what Dung’s complete semantics accept at least credulously

Computational Trust in Web Content Quality: A Comparative Evalutation on the Wikipedia Project

The problem of identifying useful and trustworthy information on the World Wide Web is becoming increasingly acute as new tools such as wikis and blogs simplify and democratize publication. It is not hard to predict that in the future the direct reliance on this material will expand and the problem of evaluating the trustworthiness of this kind of content become crucial. The Wikipedia project represents the most successful and discussed example of such online resources. In this paper we present a method to predict Wikipedia articles trustworthiness based on computational trust techniques and a deep domain-specific analysis. Our assumption is that a deeper understanding of what in general defines high-standard and expertise in domains related to Wikipedia – i.e. content quality in a collaborative environment – mapped onto Wikipedia elements would lead to a complete set of mechanisms to sustain trust in Wikipedia context. We present a series of experiment. The first is a study-case over a specific category of articles; the second is an evaluation over 8 000 articles representing 65% of the overall Wikipedia editing activity. We report encouraging results on the automated evaluation of Wikipedia content using our domain-specific expertise method. Finally, in order to appraise the value added by using domain-specific expertise, we compare our results with the ones obtained with a pre-processed cluster analysis, where complex expertise is mostly replaced by training and automatic classification of common features

Ranking Semantics Based on Subgraphs Analysis

An abstract argumentation framework [15] consists of a direct graph where nodes represent arguments and arrows represent an attack relation among arguments. A semantics is used to evaluate arguments’ acceptability. In the labelling approach [7], this evaluation is done by assigning to each argument a label in, out or undec, meaning that the argument is considered consistently acceptable, non-acceptable or undecided (i.e. no decision can be taken on arguments’ acceptability)

Towards a Computational Analysis of Probabilistic Argumentation Frameworks

In this paper we analyze probabilistic argumentation frameworks (PAFs), defined as an extension of Dung abstract argumentation frameworks in which each argument n is asserted with a probability p(n). The debate around PAFs has so far centered on their theoretical definition and basic properties. This work contributes to their computational analysis by proposing a first recursive algorithm to compute the probability of acceptance of each argument under grounded and preferred semantics, and by studying the behavior of PAFs with respect to reinstatement, cycles and changes in argument structure. The computational tools proposed may provide strategic information for agents selecting the next step in an open argumentation process and they represent a contribution in the debate about gradualism in abstract argumentation

Computing the Grounded Semantics in all the Subgraphs of an Argumentation Framework: an Empirical Evaluation

Given an argumentation framework – with a finite set of arguments and the attack relation identifying the graph – we study how the grounded labelling of a generic argument a varies in all the subgraphs of . Since this is an intractable problem of above-polynomial complexity, we present two non-naïve algorithms to find the set of all the subgraphs where the grounded semantic assigns to argument a specific label . We report the results of a series of empirical tests over graphs of increasing complexity. The value of researching the above problem is two-fold. First, knowing how an argument behaves in all the subgraphs represents strategic information for arguing agents. Second, the algorithms can be applied to the computation of the recently introduced probabilistic argumentation frameworks

The Terror Network Industrial Complex: A Measurement and Analysis of Terrorist Networks and War Stocks

This paper presents a measurement study and analysis of the structure of multiple Islamic terrorist networks to determine if similar characteristics exist between those networks. We examine data gathered from four terrorist groups: Al-Qaeda, ISIS, Lashkar-e-Taiba (LeT) and Jemaah Islamiyah (JI) consisting of six terror networks. Our study contains 471 terrorists’ nodes and 2078 links. Each terror network is compared in terms efficiency, communication and composition of network metrics. The paper examines the effects these terrorist attacks had on US aerospace and defence stocks (herein War stocks). We found that the Islamic terror groups increase recruitment during the planned attacks, communication increases during and after the attacks between the subordinate terrorists and low density is a common feature of Islamic terrorist groups. The Al- Qaeda organisation structure was the most complex and superior in terms of secrecy, diameter, clustering, modularity and density. Jemaah Islamiyah followed a similar structure but not as superior. The ISIS and LeT organisational structures were more concerned with the efficiency of the operation rather than secrecy. We found that war stocks prices and the S+P 500 were lower the day after the attacks, however, the war stocks slightly outperformed the S+P 500 the day after the attacks. Further, we found that war stock prices were significantly lower one month after the terrorist attacks but the S+P 500 rebounded one month later

Design and Evaluation of an Adventure Videogame Based in the History of Mathematics

The present paper describes the design and evaluation of an adventure videogame developed to cover the mathematics primary school curriculum. The narrative of the game is based in the history of mathematics and, to win, the player needs to travel through time, starting from the ancient Egypt and finishing at the modern world. To achieve that, the player interacts with real-life characters, such as Pythagoras of Samos, learning about their contributions to the field and using this knowledge to solve puzzles. The aim of the research presented in this paper is to understand the effects of the game on students’ mathematics performance and levels of mathematics anxiety, a clinical condition where feelings of tension emerge during the manipulation of numbers. The game was tested by children from the first and second classes of Irish primary schools (n = 88). Students played the game for 3 weeks on weekly sessions of 45 min to 1 h. The experiment had a pre post-test design and students answered the Modified Abbreviated Math Anxiety Scale (mAMAS), and a mathematics test designed based on the content of the game. Statistical analysis suggested the game significantly improves students’ mathematics performance. However, it increases the levels of mathematics anxiety on female students, opening discussion for considering what aspects of game design influences the levels of mathematics anxiety for this specific group

Trust-Based Techniques for Collective Intelligence in Social Search Systems.

A key-issue for the effectiveness of collaborative decision support systems is the problem of the trustworthiness of the entities involved in the process. Trust has been always used by humans as a form of collective intelligence to support effective decision making process. Computational trust models are becoming now a popular technique across many applications such as cloud computing, p2p networks, wikis, e-commerce sites, social network. The chapter provides an overview of the current landscape of computational models of trust and reputation, and it presents an experimental study case in the domain of social search, where we show how trust techniques can be applied to enhance the quality of social search engine predictions

Beyond reasonable doubt: a proposal for undecidedness blocking in abstract argumentation

In Dung’s abstract semantics, the label undecided is always propagated from the attacker to the attacked argument, unless the latter is also attacked by an accepted argument. In this work we propose undecidedness blocking abstract argumentation semantics where the undecided label is confined to the strong connected component where it was generated and it is not propagated to the other parts of the argumentation graph. We show how undecidedness blocking is a fundamental reasoning pattern absent in abstract argumentation but present in similar fashion in the ambiguity blocking semantics of Defeasible logic, in the beyond reasonable doubt legal principle or when someone gives someone else the benefit of the doubt. The resulting semantics, called SCC-void semantics, are defined using an SCC-recursive schema. The semantics are conflict-free and non-admissible, but they incorporate a more relaxed defence-based notion of admissibility. They allow reinstatement and they credulously accept what the corresponding Dung’s complete semantics accepts at least credulously

A Proposal to Embed the In Dubio Pro Reo Principle into Abstract Argumentation Semantics based on Topological Ordering and Undecidedness Propagation

Abstract. In this paper we discuss how the in dubio pro reo principle and the corresponding standard of proof beyond reasonable doubt can be modelled in abstract argumentation. The in dubio pro reo principle protects arguments against attacks from doubtful arguments. We identify doubtful arguments with a subset of undecided arguments, called active undecided arguments, consisting of cyclic arguments responsible for generating the undecided situation. We obtain the standard of proof beyond reasonable doubt by imposing that attacks from doubtful undecided arguments are not enough to change the acceptability status of an attacked argument (the reo). The resulting semantics, called SCCvoid semantics, are defined using a SCC-recursive schema. The semantics are conflict-free, non-admissible (in Dung’s sense), but employing a more relaxed defence-based notion of admissibility; they allow reinstatement and they accept credulously what the corresponding complete semantics accepts at least credulously