Online Handbook of Argumentation for AI: Volume 3

Editors: Federico Castagna, Francesca Mosca, Jack Mumford, Stefan Sarkadi and Andreas Xydis.This volume contains revised versions of the papers selected for the third 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

Online Handbook of Argumentation for AI: Volume 2

Editors: Federico Castagna, Francesca Mosca, Jack Mumford, Stefan Sarkadi and Andreas Xydis.This volume contains revised versions of the papers selected for the second 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

In memoriam Douglas N. Walton: the influence of Doug Walton on AI and law

Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work

Informal Logic: A 'Canadian' Approach to Argument

The informal logic movement began as an attempt to develop – and teach – an alternative logic which can account for the real life arguing that surrounds us in our daily lives – in newspapers and the popular media, political and social commentary, advertising, and interpersonal exchange. The movement was rooted in research and discussion in Canada and especially at the University of Windsor, and has become a branch of argumentation theory which intersects with related traditions and approaches (notably formal logic, rhetoric and dialectics in the form of pragma-dialectics). In this volume, some of the best known contributors to the movement discuss their views and the reasoning and argument which is informal logic’s subject matter. Many themes and issues are explored in a way that will fuel the continued evolution of the field. Federico Puppo adds an insightful essay which considers the origins and development of informal logic and whether informal logicians are properly described as a “school” of thought. In considering that proposition, Puppo introduces readers to a diverse range of essays, some of them previously published, others written specifically for this volume

Teaching as Analogous Personalization: A pragmatic inquiry into expert teachers' process for fostering synchrony in educational dialogs, in post-secondary writing

Descriptive understandings of what human learning is, and so normative expectations of what teachers can and should do as educational leaders, has shifted greatly in society over the past century. The learning metaphors have moved from mechanical transfer to organic transformation; the educational approaches have moved from behavioral response-training to social-emotional facilitating: encouraging students not merely to repeat experts but to think like members in those knowledge-based communities, not merely to mimic disciplines' methods but to participate personally in the ongoing discourse of those fields. In an immediate sense, this shift is progress. Yet, in a larger sense, it is merely cycling back to acknowledge an old and persistent thread of practical wisdom among educators: that people learn complexly as emotional-social-intellectual creatures, and so that a teacher's work is to entice interest and effort, to foster a sense of belonging and trust, and to persuade students toward personally connecting with and valuing those same integral parts of a subject-matter that the teacher has already beneficially personalized for themselves. This longstanding rhetorical and pragmatic view of a teacher's educational role is now being supported directly by empirical research that shows the sense-bound, neurologically integrated, socially attuned, identity-and-meaning motivated character of human feelings, thoughts, and dispositions. I introduce the term “analogous personalization” to capture this synthetic (experience-based, scientifically supported) understanding of teaching as complexly social-emotional, intellectual, persuasive work. I then focus on educational dialogs—specifically within post-secondary writing-based courses—as a means of exploring how expert teachers foster synchrony between their own and their students' personal connections to (i.e., emotional inclination toward, social affiliation with, intellectual/practical understanding of) subject-matter. First, this dissertation offers a synthetic overview of some emergent mind-brain-body findings, and points out the fundamental educational realities that those findings substantiate. On that foundation, it next overviews insights from the field of rhetoric-and-writing about how teachers can usefully conceptualize the learner-knowledge-environment relationship from a dialogic perspective, to achieve effective (intentional, situated, synchronous) educational exchanges. Building from those scientific and practical literatures, it offers a flexible research method for studying the pragmatic arc of an educational exchange (from teacher intention to student take-away): by using the teacher's own personal, practical, principled framework of educational ideals and approaches; comparing their stated intentions with students' stated learning experiences, and tracing the arc of that educational dialog through actual classroom recordings. Finally, it enlists this radically situated research method to analyze three expert university writing teachers' practices: their idiosyncratic understandings of a teacher's role (from their own perspective); their experience-based manner of forming learning-centered relationships with students (from my observing perspective); and their apparent, persuasive self-investment in the course's subject-matter and the students' learning (from students' perspectives). It concludes with observations about the role of a teacher's sincerity (both practiced and perceived) in developing professional expertise and achieving synchrony with students in educational exchanges

Negotiating Socially Optimal Allocations of Resources with Argumentation

The resource allocation problem of multi-agent systems is the problem of deciding how to allocate resources, controlled by agents, to agents within a given system. Agents typically have preferences over alternative allocations of resources. These preferences may be derived from the agents’ goals, which can be fulfilled by different plans (sets of resources). The problem arises because agents may not be able to fulfil their goals without being re-allocated resources controlled by other agents and agents may have conflicting preferences over allocations. Examples of the resource allocation problem include electronic commerce (where resources are commodities equipped with prices), the grid (where resources are computational entities equipped with computational power), and scheduling and timetabling (where resources may be tasks with costs). The focus in this thesis is distributed decision-making amongst agents, whereby agents actively participate in computing re-allocations, starting from initial allocations which may or may not fulfil their goals. A re-allocation is arrived at by means of local negotiation steps wherein resources change hands between the agents involved in the negotiations. The negotiation method of choice in this thesis is argumentation-based negotiation supported by assumption-based argumentation. This method allows agents to work towards their goals despite incomplete information regarding the goals of and resources allocated to other agents, to share knowledge, thereby eliminating unknowns, and to resolve conflicts within themselves and between one another which may arise because of inconsistent information. Solutions generated by a resource allocation mechanism may be ranked according to how they affect the individual welfare of the agents as well as the overall social welfare of the agent society, according to different notions of social welfare borrowed from economics. The argumentation-based negotiation mechanism we propose guarantees, for the problem domain of interest in this thesis, that negotiations between agents always terminate converging to a solution. Moreover, the mechanism guarantees that solutions reached optimise the welfare of the individual agents as well as the agent society as a whole according to Pareto optimal and utilitarian notions of social welfare

Automatic extraction and structure of arguments in legal documents

A argumentação desempenha um papel fundamental na comunicação humana ao formular razões e tirar conclusões. Desenvolveu-se um sistema automático para identificar argumentos jurídicos de forma eficaz em termos de custos a partir da jurisprudência. Usando 42 leis jurídicas do Tribunal Europeu dos Direitos Humanos (ECHR), anotou-se os documentos para estabelecer um conjunto de dados “padrão-ouro”. Foi então desenvolvido e testado um processo composto por 3 etapas para mineração de argumentos. A primeira etapa foi avaliar o melhor conjunto de recursos para identificar automaticamente as frases argumentativas do texto não estruturado. Várias experiencias foram conduzidas dependendo do tipo de características disponíveis no corpus, a fim de determinar qual abordagem que produzia os melhores resultados. No segundo estágio, introduziu-se uma nova abordagem de agrupamento automático (para agrupar frases num argumento legal coerente), através da utilização de dois novos algoritmos: o “Algoritmo de Identificação do Grupo Apropriado”, ACIA e a “Distribuição de orações no agrupamento de Cluster”, DSCA. O trabalho inclui também um sistema de avaliação do algoritmo de agrupamento que permite ajustar o seu desempenho. Na terceira etapa do trabalho, utilizou-se uma abordagem híbrida de técnicas estatísticas e baseadas em regras para categorizar as orações argumentativas. No geral, observa-se que o nível de precisão e utilidade alcançado por essas novas técnicas é viável como base para uma estrutura geral de argumentação e mineração; Abstract: Automatic Extraction and Structure of Arguments in Legal Documents Argumentation plays a cardinal role in human communication when formulating reasons and drawing conclusions. A system to automatically identify legal arguments cost-effectively from case-law was developed. Using 42 legal case-laws from the European Court of Human Rights (ECHR), an annotation was performed to establish a ‘gold-standard’ dataset. Then a three-stage process for argument mining was developed and tested. The first stage aims at evaluating the best set of features for automatically identifying argumentative sentences within unstructured text. Several experiments were conducted, depending upon the type of features available in the corpus, in order to determine which approach yielded the best result. In the second stage, a novel approach to clustering (for grouping sentences automatically into a coherent legal argument) was introduced through the development of two new algorithms: the “Appropriate Cluster Identification Algorithm”,(ACIA) and the “Distribution of Sentence to the Cluster Algorithm” (DSCA). This work also includes a new evaluation system for the clustering algorithm, which helps tuning it for performance. In the third stage, a hybrid approach of statistical and rule-based techniques was used in order to categorize argumentative sentences. Overall, it’s possible to observe that the level of accuracy and usefulness achieve by these new techniques makes it viable as the basis of a general argument-mining framework

Planning multisentential English text using communicative acts

The goal of this research is to develop explanation presentation mechanisms for knowledge based systems which enable them to define domain terminology and concepts, narrate events, elucidate plans, processes, or propositions and argue to support a claim or advocate action. This requires the development of devices which select, structure, order and then linguistically realize explanation content as coherent and cohesive English text. With the goal of identifying generic explanation presentation strategies, a wide range of naturally occurring texts were analyzed with respect to their communicative sttucture, function, content and intended effects on the reader. This motivated an integrated theory of communicative acts which characterizes text at the level of rhetorical acts (e.g., describe, define, narrate), illocutionary acts (e.g., inform, request), and locutionary acts (e.g., ask, command). Taken as a whole, the identified communicative acts characterize the structure, content and intended effects of four types of text: description, narration, exposition, argument. These text types have distinct effects such as getting the reader to know about entities, to know about events, to understand plans, processes, or propositions, or to believe propositions or want to perform actions. In addition to identifying the communicative function and effect of text at multiple levels of abstraction, this dissertation details a tripartite theory of focus of attention (discourse focus, temporal focus, and spatial focus) which constrains the planning and linguistic realization of text. To test the integrated theory of communicative acts and tripartite theory of focus of attention, a text generation system TEXPLAN (Textual EXplanation PLANner) was implemented that plans and linguistically realizes multisentential and multiparagraph explanations from knowledge based systems. The communicative acts identified during text analysis were formalized as over sixty compositional and (in some cases) recursive plan operators in the library of a hierarchical planner. Discourse, temporal, and spatial focus models were implemented to track and use attentional information to guide the organization and realization of text. Because the plan operators distinguish between the communicative function (e.g., argue for a proposition) and the expected effect (e.g., the reader believes the proposition) of communicative acts, the system is able to construct a discourse model of the structure and function of its textual responses as well as a user model of the expected effects of its responses on the reader's knowledge, beliefs, and desires. The system uses both the discourse model and user model to guide subsequent utterances. To test its generality, the system was interfaced to a variety of domain applications including a neuropsychological diagnosis system, a mission planning system, and a knowledge based mission simulator. The system produces descriptions, narrations, expositions, and arguments from these applications, thus exhibiting a broader range of rhetorical coverage than previous text generation systems