多智能体系统中基于承诺的协商语义

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Annals of Mathematics and Artificial Intelligence Pub Date : 2023-07-08 DOI:10.1007/s10472-023-09875-w
Phillip Sloan, Nirav Ajmeri
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引用次数: 0

摘要

协商是多代理系统中的一种重要互动形式。协商能让代理就目标或行动计划达成一致。目前的协商方法使用传统的交互协议,这些协议无法捕捉到交互的规范意义,而且往往限制了代理的自主性。这些传统的协商方法也很难明确规定责任。本文试图通过使用规范性承诺来弥补谈判过程中在保持自主性和捕捉责任方面的不足。我们提出了基于承诺的谈判语义 Nala。Nala 使用承诺为代理互动提供规范意义。承诺的性质有助于通过违反所创建的承诺来追究责任。我们通过一个案例研究来说明 Nala 的用法,该案例研究使用了一个游戏场景,在该游戏场景中,代理参与谈判,以便在一个研究受限的环境中实现他们的目标。
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Commitment-based negotiation semantics for accountability in multi-agent systems

Negotiation is a key form of interaction in multi-agent systems. Negotiation enables agents to come to a mutual agreement about a goal or plan of action. Current negotiation approaches use traditional interaction protocols which do not capture the normative meaning of interactions and often restrict agent autonomy. These traditional negotiation approaches also have difficulty specifying accountability. This paper seeks to address this gap in maintaining autonomy and capturing accountability during negotiation through the use of normative commitments. We propose Nala, a commitment-based negotiation semantics. Nala uses commitments to provide normative meaning to agent interactions. The nature of commitments support in capturing accountability through the violation of created commitments. We illustrate Nala’s usage via a case study using a game scenario where agents participate in negotiation to bring about their goals in a research constrained environment.

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来源期刊
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
3.00
自引率
8.30%
发文量
37
审稿时长
>12 weeks
期刊介绍: Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning. The journal features collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages), which focus on one topic and have one or more guest editors. Annals of Mathematics and Artificial Intelligence hopes to influence the spawning of new areas of applied mathematics and strengthen the scientific underpinnings of Artificial Intelligence.
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