从人类论证角度介绍计算论证研究

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Ramon Ruiz-Dolz, Stella Heras, Ana García-Fornes
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引用次数: 0

摘要

计算论证研究如何从计算的角度来处理人类的论证推理。人类论证是一个复杂的过程,已经从不同的角度(例如,哲学或语言学)进行了研究,涉及到纯推理之外的许多不同方面,例如情感,价值观,社会背景和实际约束的作用,这些在计算方法中经常被忽视。人类论证的异质性存在于计算论证研究中,以不同任务的形式分别接近论证的主要阶段。随着研究人员对人工智能的兴趣日益浓厚,我们认为为计算论证研究领域提供指导是非常重要的。因此,在本文中,我们从人类如何辩论的角度,提出了计算论证的总体概述。为此目的,产生了以下贡献:(i)计算论证研究的一致结构与人类论证过程的映射;(ii)对计算论证所处理的任务及其协同作用的集体理解;彻底审查每项任务的重要进展;(iv)对计算论证研究的未来趋势和该领域的相关公开挑战进行分析和分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An introduction to computational argumentation research from a human argumentation perspective

An introduction to computational argumentation research from a human argumentation perspective

Computational Argumentation studies how human argumentative reasoning can be approached from a computational viewpoint. Human argumentation is a complex process that has been studied from different perspectives (e.g., philosophical or linguistic) and that involves many different aspects beyond pure reasoning, such as the role of emotions, values, social contexts, and practical constraints, which are often overlooked in computational approaches to argumentation. The heterogeneity of human argumentation is present in Computational Argumentation research, in the form of various tasks that approach the main phases of argumentation individually. With the increasing interest of researchers in Artificial Intelligence, we consider that it is of great importance to provide guidance on the Computational Argumentation research area. Thus, in this paper, we present a general overview of Computational Argumentation, from the perspective of how humans argue. For that purpose, the following contributions are produced: (i) a consistent structure for Computational Argumentation research mapped with the human argumentation process; (ii) a collective understanding of the tasks approached by Computational Argumentation and their synergies; (iii) a thorough review of important advances in each of these tasks; and (iv) an analysis and a classification of the future trends in Computational Argumentation research and relevant open challenges in the area.

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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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