RGS $^\oplus $:协作机器人的RDF图同步

IF 2 3区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Autonomous Agents and Multi-Agent Systems Pub Date : 2023-11-24 DOI:10.1007/s10458-023-09629-2

Cyrille Berger, Patrick Doherty, Piotr Rudol, Mariusz Wzorek

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引用次数: 0

摘要

在协作机器人的背景下，分布式态势感知对于支持机器人和人类代理团队中的集体智能至关重要，它可以用于个人和集体决策支持。这在与紧急救援和危机管理有关的应用中尤其重要。在作战任务中，不同类型的机器人和人类以不同的方式逐步收集数据和知识。本文的目的是描述一个叫做RGS $^\oplus $的RDF图同步系统。假设一组动态代理提供或检索存储在其本地RDF图中的知识，这些知识在代理之间不断同步。RGS $^\oplus $系统设计用于处理不可靠的通信，并且不依赖于静态的集中式基础设施。它能够尽可能及时地同步知识，并允许代理在增量获取知识时访问知识。对RGS $^\oplus $系统进行了更深入的实证分析，显示了其效率和功效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

$RGS$^\oplus $: RDF graph synchronization for collaborative robotics$

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RGS$^\oplus $: RDF graph synchronization for collaborative robotics

In the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge is gathered incrementally and in different ways by heterogeneous robots and humans. The purpose of this paper is to describe an RDF Graph Synchronization System called RGS$^\oplus $. It is assumed that a dynamic set of agents provide or retrieve knowledge stored in their local RDF Graphs which are continuously synchronized between agents. The RGS$^\oplus $ System was designed to handle unreliable communication and does not rely on a static centralized infrastructure. It is capable of synchronizing knowledge as timely as possible and allows agents to access knowledge while it is incrementally acquired. A deeper empirical analysis of the RGS$^\oplus $ System is provided that shows both its efficiency and efficacy.

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来源期刊

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

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.

RGS \(^\oplus \):协作机器人的RDF图同步

摘要