Computational Argumentation Research Articles

A Decision Support Tool for Agricultural Applications Based on Computational Social Choice and Argumentation

In the current article, the authors describe an applied procedure to support collective decision making for applications in agriculture. An extended 2-page abstract of this paper has been accepted by the EFITA WCCA congress and this manuscript is an extended version of this submission. The problem the authors are facing in this paper is how to reach the best decision regarding issues coming from agricultural engineering with the aid of Computational Social Choice (CSC) and Argumentation Framework (AF). In the literature of decision-making, several approaches from the domains of CSC and AF have been used autonomously to support decisions. It is our belief that with the combination of these two fields the authors can propose socially fair decisions which take into account both (1) the involved agents' preferences and (2) the justifications behind these preferences. Therefore, this article implements a software tool for decision-making which is composed of two main systems, i.e., the social choice system and the deliberation system. In this article, the authors describe thoroughly the social choice system of our tool and how it can be applied to different alternatives on the valorization of materials coming from agriculture. As an example, that is demonstrated an application of our tool in the context of Ecobiocap European project where several decision problems are to be addressed. These decision problems consist in finding the best solutions for questions regarding food packaging and end-of-life management.

Plausible Argumentation in Eikotic Arguments: The Ancient Weak Versus Strong Man Example

In this paper it is shown how plausible reasoning of the kind illustrated in the ancient Greek example of the weak and strong man can be analyzed and evaluated using a procedure in which the pro evidence is weighed against the con evidence using formal, computational argumentation tools. It is shown by means of this famous example how plausible reasoning is based on an audience’s recognition of situations of a type they are familiar with as normal and comprehensible in their shared common knowledge. The paper extends previous work on this example by using three new multiagent argumentation schemes closely related to the scheme for argument from negative consequences.

A general semi-structured formalism for computational argumentation: Definition, properties, and examples of application

In the field of computational argumentation several formalisms featuring different levels of abstraction and focusing on different aspects of the argumentation process have been developed. Their combined use, necessary to achieve a comprehensive formal coverage of the argumentation phenomenon, gives rise to a nontrivial interplay between different abstraction levels, so that counterintuitive or undesirable outcomes may result from the combination of formalisms which appear to be well-behaved when considered in isolation. To address this problem we introduce a semi-structured formalism for argumentation, called LAF-ensembles, capturing a set of essential features of structured arguments and define a class of set based argumentation frameworks appropriate to support a semantic assessment of arguments for LAF-ensembles. It is shown that, under suitable assumptions, the combination of a LAF-ensemble and of an appropriate argumentation framework is guaranteed to produce justification outcomes satisfying a set of essential requirements. The generality and usefulness of the proposed approach are demonstrated by illustrating its ability to capture as instances and enhance two structured argumentation formalisms from the literature, namely Vreeswijk's abstract argument systems and Modgil and Prakken's ASPIC+. In particular, a revised version of the latter formalism, properly dealing with generic contrariness and solving significant technical limitations of ASPIC+, is proposed.

On linear independence of trigonometric numbers

A necessary and sufficient condition is established for 1, cos(πr1), and cos(πr2) to be rationally independent, where r1, r2 are rational numbers. The elementary computational argument yields linear independence over larger number fields as well.

Argument Invention with the Carneades Argumentation System

Argument invention (inventio) has traditionally been regarded as one of the five main components of rhetoric, but has remained an ambiguous, vague and highly contested concept, made even more confusing by its dependence on the Aristotelian topics, supposedly the places in which the rhetorical persuader can find arguments useful to support or attack a claim. The advent of two recently developed computational tools for argument invention, the Carneades Argumentation System and IBM’s Watson Debater tool, calls for a rethinking of the notion of argument invention in line with the state of the art of formal and computational argumentation systems in artificial intelligence. The role of argumentation schemes is an important part of this investigation into argument invention.

A study measuring the impact of shared decision making in a human-robot team

This paper presents the results of a user study in which the impact of sharing decision making in a human-robot team was measured. In the experiments outlined here, a human and robot play a game together in which the robot searches an arena for items, with input from the human, and the human-robot team earns points for finding and correctly identifying the items. The user study reported here involved 60 human subjects. Each subject interacted with two different robots. With one robot, the human acted as a supervisor: the human issued commands and the robot obeyed. With the other robot, the human acted as a collaborator: the human and robot shared decisions and were required to reach agreement about the robot’s actions in the arena before any actions were taken, facilitated using computational argumentation. Objective performance metrics were collected and analyzed for both types of human-robot team, as well subjective feedback from human subjects regarding attitudes toward working with a robot. The objective results showed significant improvement in performance metrics with the human-as-collaborator pairs versus the human-as-supervisor pairs. Subjective results demonstrated significant differences across many subjective measures and indicated a distinct preference for the human-as-collaborator mode. The primary contribution of this work lies in the demonstration and evaluation of a computational argumentation approach to human-robot interaction, particularly in proving the efficacy of this approach over a less autonomous mode of interaction.

The Argument Web: an Online Ecosystem of Tools, Systems and Services for Argumentation

The Argument Web is maturing as both a platform built upon a synthesis of many contemporary theories of argumentation in philosophy and also as an ecosystem in which various applications and application components are contributed by different research groups around the world. It already hosts the largest publicly accessible corpora of argumentation and has the largest number of interoperable and cross compatible tools for the analysis, navigation and evaluation of arguments across a broad range of domains, languages and activity types. Such interoperability is key in allowing innovative combinations of tool and data reuse that can further catalyse the development of the field of computational argumentation. The aim of this paper is to summarise the key foundations, the recent advances and the goals of the Argument Web, with a particular focus on demonstrating the relevance to, and roots in, philosophical argumentation theory.

Emotions and personality traits in argumentation: An empirical evaluation1

Argumentation is a mechanism to support different forms of reasoning such as decision making and persuasion and always cast under the light of critical thinking. In the latest years, several computational approaches to argumentation have been proposed to detect conflicting information, take the best decision with respect to the available knowledge, and update our own beliefs when new information arrives. The common point of all these approaches is that they assume a purely rational behavior of the involved actors, be them humans or artificial agents. However, this is not the case as humans are proved to behave differently, mixing rational and emotional attitudes to guide their actions. Some works have claimed that there exists a strong connection between the argumentation process and the emotions felt by people involved in such process. We advocate a complementary, descriptive and experimental method, based on the collection of emotional data about the way human reasoners handle emotions during debate interactions. Across different debates, people’s argumentation in plain English is correlated with the emotions automatically detected from the participants, their engagement in the debate, and the mental workload required to debate. Results show several correlations among emotions, engagement and mental workload with respect to the argumentation elements. For instance, when two opposite opinions are conflicting, this is reflected in a negative way on the debaters’ emotions. Beside their theoretical value for validating and inspiring computational argumentation theory, these results have applied value for developing artificial agents meant to argue with human users or to assist users in the management of debates.

The Tweety Library Collection for Logical Aspects of Artificial Intelligence and Knowledge Representation

Tweety is a collection of Java libraries that provides a general interface layer for doing research in and working with different knowledge representation formalisms such as classical logics, conditional logics, probabilistic logics, and computational argumentation. It is designed in such a way that tasks like representing and reasoning with knowledge bases inside the programming environment are realizable in a common manner. Furthermore, Tweety contains libraries for dealing with agents, multi-agent systems, and dialog systems for agents, as well as belief revision, preference reasoning, preference aggregation, and action languages. A series of utility libraries that deal with e. g. mathematical optimization complement the collection.

Erratum to: Arguments from authority and expert opinion in computational argumentation systems

Erratum to: Arguments from authority and expert opinion in computational argumentation systems

Arguments from authority and expert opinion in computational argumentation systems

In this paper we show that an essential aspect of solving the problem of uncritical acceptance of expert opinions that is at the root of the ad verecundiam fallacy is the need to disentangle argument from expert opinion from another kind of appeal to authority. Formal and computational argumentation systems enable us to analyze the fault in which an error has occurred by virtue of a failure to meet one or more of the requirements of the argumentation scheme from argument from expert opinion. We present a method for enhancing this capability by showing how arguments from expert opinion are related to, but different from, arguments from deontic authority.

Exploiting Parallelism for Hard Problems in Abstract Argumentation

Abstract argumentation framework (AF) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and enumeration problems associated to AFs are missing, thus limiting the efficacy of argumentation-based approaches in real domains. In this paper, we present an algorithm for enumerating the preferred extensions of abstract argumentation frameworks which exploits parallel computation. To this purpose, the SCC-recursive semantics definition schema is adopted, where extensions are defined at the level of specific sub-frameworks. The algorithm shows significant performance improvements in large frameworks, in terms of number of solutions found and speedup.

Quaestio-it.com: a social intelligent debating platform

Information sharing between online users has altered the way we seek and find information. Users have at their disposal a wide range of tools for exchanging opinions and engaging in discussions. This creates a vast amount of information and the need for a more strict structure and semantics in order to take full advantage of the information and automatically extract useful conclusions to support decision-making. In this paper we describe a framework, based on computational argumentation, for modeling and analysing social discussions, and demonstrate a question-and-answer web application, based on this framework, offering debating infrastructure for opinion exchanges between users and providing support for extracting intelligent answers to user-posed questions.

Trust and argumentation in multi-agent systems

This survey is the first to review the combination of computational trust and argumentation. The combination of the two approaches seems like a natural match, with the two areas tackling different aspects of reasoning in an uncertain, social environment. We discuss the different areas of research and describe the approaches taken so far, analysing both how they address the problems and the challenges that are unaddressed.

On a razor's edge: evaluating arguments from expert opinion

This paper takes an argumentation approach to find the place of trust in a method for evaluating arguments from expert opinion. The method uses the argumentation scheme for argument from expert opinion along with its matching set of critical questions. It shows how to use this scheme in three formal computational argumentation models that provide tools to analyse and evaluate instances of argument from expert opinion. The paper uses several examples to illustrate the use of these tools. A conclusion of the paper is that from an argumentation point of view, it is better to critically question arguments from expert opinion than to accept or reject them based solely on trust.

On logical specifications of the Argument Interchange Format

The Argument Interchange Format (AIF) has been devised in order to support the interchange of ideas and data between different projects and applications in the area of computational argumentation. The AIF presents an abstract ontology for argumentation which serves as an interlingua between various reifications that consist of more concrete argumentation languages. In this paper, we aim to give a logical reification of the AIF ontology, by defining translations between the ontology’s language and the formal ASPIC framework for argumentation. We thus lay foundations for interrelating formal logic-based approaches to argumentation captured by the general ASPIC framework, and the wider class of AIF reifications, including those that are more informal and user orientated.

An appreciation of John Pollock's work on the computational study of argument

John Pollock (1940–2009) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first formal systems for argumentation-based inference and he put many issues on the research agenda that are still relevant for the argumentation community today. This paper presents an appreciation of Pollock's work on defeasible reasoning and its relevance for the computational study of argument. In our opinion, Pollock deserves to be remembered as one of the founding fathers of the field of computational argument, while, moreover, his work contains important lessons for current research in this field, reminding us of the richness of its object of study.

Argudas: lessons for argumentation in biology based on a gene expression use case.

BackgroundIn situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both sides - the statement is true and, the statement is false - then the most powerful argument is used. In this work the computer is asked to debate whether or not a gene is expressed in a particular mouse anatomical structure. The information generated during the debate can be passed to the biological end-user, enabling their own decision-making process.ResultsThis paper examines the evolution of a system, Argudas, which tests using computational argumentation in an in situ gene hybridisation gene expression use case. Argudas reasons using information extracted from several different online resources that publish gene expression information for the mouse. The development and evaluation of two prototypes is discussed. Throughout a number of issues shall be raised including the appropriateness of computational argumentation in biology and the challenges faced when integrating apparently similar online biological databases.ConclusionsFrom the work described in this paper it is clear that for argumentation to be effective in the biological domain the argumentation community need to develop further the tools and resources they provide. Additionally, the biological community must tackle the incongruity between overlapping and adjacent resources, thus facilitating the integration and modelling of biological information. Finally, this work highlights both the importance of, and difficulty in creating, a good model of the domain.

Fully Bayesian analysis of the relevance vector machine with an extended hierarchical prior structure

This paper proposes an extended hierarchical hyperprior structure for kernel regression with the goal of solving the so-called Neyman–Scott problem inherent in the now very popular relevance vector machine (RVM). We conjecture that the proposed prior helps achieve consistent estimates of the quantities of interest, thereby overcoming a limitation of the original RVM for which the estimates of the quantities of interest are shown to be inconsistent. Unlike the majority of other authors in this area who typically use an empirical Bayes approach for RVM, we adopt a fully Bayesian approach. Our consistency claim at this stage remains only a conjecture, to be proved theoretically in a subsequent paper. However, we use a computational argument to demonstrate the merits of the proposed solution.

Reports on the AAAI 2009 Fall Symposia

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Computational Argumentation, and (7) Virtual Healthcare Interaction.