An empirical study of a deliberation dialogue system

Lecture Notes in Computer Science, 2011

Agents engage in deliberation dialogues to collectively decide on a course of action. To solve conflicts of opinion that arise, they can question claims and supply arguments. Existing models fail to capture the interplay between the provided arguments as well as successively selecting a winner from the proposals. This paper introduces a general framework for agent deliberation dialogues that uses an explicit reply structure to produce coherent dialogues, guides in outcome selection and provide pointers for agent strategies.

Argument & Computation, 2016

Models of deliberative dialogue are fundamental for developing autonomous systems that support human practical reasoning. The question discussed in this paper is whether existing models are able to capture the complexity and richness of natural deliberation. In real-world contexts, circumstances relevant to the decision can change rapidly. We reflect on today's leading model of deliberation dialogue and we propose an extension to capture how newly exchanged information about changing circumstances may shape the dialogue. Moreover, in natural deliberation, a dialogue may be successful even if a decision on what to do has not been made. A set of criteria is proposed to address the problem of when to close off the practical reasoning phase of dialogue. We discuss some measures for evaluating the success of a dialogue after closure and we present some initial efforts to introduce the new deliberation features within an existing model of agent dialogue. We believe that our extended model of dialogue may contribute to representing that richness of natural deliberative dialogue that is yet to be addressed in existing models of agent deliberation.

Lecture Notes in Computer Science, 2014

Lecture Notes in Computer Science, 2012

Increasingly research into the uses of argumentation in multiagent dialogues takes an experimental approach. Such studies explore how agents can successfully employ argumentation besides the best and worst case situations of formal analysis. While a vital part in these experiments is influenced by the scenarios from which dialogues are generated, there is very little research on how these can be generated in a meaningful way, respecting the characteristics of the underlying dialogue problem. This paper proposes, by means of an example system for deliberation dialogues, a methodology for the construction and evaluation of a scenario generation process. It is shown how scenarios can accomodate argumentation with structured arguments and how it is tested whether the generated scenarios are interesting for experimentation.

2007

This paper focuses of the group judgments obtained from a committee of agents that use deliberation. The deliberative process is realized by an argumentation framework called AMAL. The AMAL framework is completely based on learning from examples: the argument preference relation, the argument generation policy, and the counterargument generation policy are case-based techniques. For join deliberation, learning agents share their experience by forming a committee to decide upon some joint decision. We experimentally show that the deliberation in committees of agents improves the accuracy of group judgments. We also show that a voting scheme based on assessing the confidence of arguments improves the accuracy of group judgments than majority voting.

Ai Communications

This paper describes a Group Decision Support System for cooperative or non-cooperative argumentative discourses. The system provides agents means of expressing and weighing their individual arguments and preferences, in order to argue for or against the selection of a certain choice. It supports defeasible and qualitative reasoning in the presence of illstructured information. Argumentation is performed through a set of discourse acts which call a variety of procedures for the propagation of information in the corresponding discussion graph. The system incorporates Case Based Reasoning to resolve current issues by using previous similar situations. Cases are not mere representations of past data, but flexible entities associated with the underlying viewpoint of an agent and the evolution of the corresponding discussion. The paper provides an object-oriented description of the elements involved, and illustrates their dependencies through a comprehensive example. 1 the term informal logic was primarily used to denote an approach to argument interpretation and evaluation that is distinct from traditional, formal logic. AI Communications 0 () 0

Computing and Informatics

Argumentation plays an important role in reasoning and allows the justification of opinions, especially when applied to collaborative decision making. Reaching consensus is not a trivial task where arguments exchanged in a dialogue and common knowledge are important for consensus. This paper presents a model of argumentative dialogue to support the formation of common knowledge in a group of agents that communicate by sending arguments, and proposes a semantics for consensus decision making. The output of the model is a weighted argumentation graph in which semantics is used to decide the preference of the group.

CEUR Workshop Proceedings, 2022

Methods of deliberative argumentation are widely employed for solving applied tasks in various fields of practical activities, where choosing a line of behaviour in a certain situation or making decisions is at stake. These methods enjoy permanent attention in contemporary education with respect to teaching argumentation and training critical thinking skills. In the last three decades, the progress in information and communication technologies has led to the development of software designed for visualization and modelling of deliberative intellectual activity for solving various kinds of practical tasks and for supporting relevant education. We propose the five (groups of) criteria for developing the software designed to model and represent deliberative argumentation, which has to be observed both in the development software and in its classification. We suggest four ontologies for such software, which will enhance implementing functions for evaluating arguments and finding solutions in such software.

Simply put, a multiagent system can be seen as a collection of autonomous agents that as a whole are able to accomplish goals beyond the reach of any of its members. Agent interaction is widely acknowledged as the feature that provides this added potential. Since many, if not all, of the attractive agent interactions can be recasted as deliberations, a formalization for this process is being actively seek.

2006

In this paper we present a prototype of a tool that demonstrates how existing limitations in ensuring an agent’s compliance to an argumentation-based dialogue protocol can be overcome. We also present the implementation of compliance enforcement components for a deliberation dialogue protocol, and an application that enables two human participants to engage in an efficiently moderated dialogue, where all inappropriate utterances attempted by an agent are blocked and prevented from inclusion within the dialogue.