为多智能体系统生成和选择组织

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Cleber J. Amaral, Jomi F. Hübner, Stephen Cranefield
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引用次数: 0

摘要

组织的设计是一项复杂而艰巨的任务。它是最近研究的主题,这些研究定义了自动执行此任务的模型。然而,现有模型通过要求组织角色的先验定义来限制可能解决方案的空间,并且通常不适合规划资源使用。本文提出了GoOrg模型,该模型使用一组目标和一组可用代理作为输入,以生成由综合组织职位组成的组织结构的不同安排。GoOrg最显著的特点是使用组织职位而不是角色,职位是自动合成的,而不是作为先验定义的输入。这些特征有助于参数化、资源规划的使用以及找到可行解决方案的机会。本文还介绍了两个模型扩展,它们定义了GoOrg如何适应不同领域的过程和约束。在围绕组织设计的各个方面中,本文讨论了模型的输入、代理的抽象和资源规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Generating and choosing organisations for multi-agent systems

Generating and choosing organisations for multi-agent systems

The design of organisations is a complex and laborious task. It is the subject of recent studies, which define models to automatically perform this task. However, existing models constrain the space of possible solutions by requiring a priori definitions of organisational roles and usually are not suitable for planning resource use. This paper presents GoOrg, a model that uses as input a set of goals and a set of available agents to generate different arrangements of organisational structures made up of synthesised organisational positions. The most distinguishing characteristics of GoOrg are the use of organisational positions instead of roles and that positions are automatically synthesised rather than required as a priori defined inputs. These characteristics facilitate the parametrisation, the use for resource planning and the chance of finding feasible solutions. This paper also introduces two model extensions, which define processes and constraints that illustrate how GoOrg suits different domains. Among aspects that surround an organisation design, this paper discusses models’ input, agents’ abstractions and resource planning.

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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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