2006
DOI: 10.1007/11875581_140
|View full text |Cite
|
Sign up to set email alerts
|

A Graph Transformation System Model of Dynamic Reorganization in Multi-agent Systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
2
0
1

Year Published

2009
2009
2020
2020

Publication Types

Select...
4

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 8 publications
0
2
0
1
Order By: Relevance
“…In [23], a graph-transformational approach for modeling reorganization in multi-agent systems is introduced. Similarly to [21], the considered multi-graphs comprise three levels: on the top level, role graphs composed of roles and their interrelations; on the bottom level, agent graphs consisting of agents and their interrelations; on the mid level, connection graphs having roles and agents as nodes, and the role competences for agents as their directed edges.…”
Section: Related Conceptsmentioning
confidence: 99%
See 1 more Smart Citation
“…In [23], a graph-transformational approach for modeling reorganization in multi-agent systems is introduced. Similarly to [21], the considered multi-graphs comprise three levels: on the top level, role graphs composed of roles and their interrelations; on the bottom level, agent graphs consisting of agents and their interrelations; on the mid level, connection graphs having roles and agents as nodes, and the role competences for agents as their directed edges.…”
Section: Related Conceptsmentioning
confidence: 99%
“…Topics in graph transformation are growing in popularity. While several concepts in the scope of graph-transformational interacting systems such as graph transformation systems with dependencies [5], distributed graph transformation [21], autonomous units [15], graph-transformational swarms [1], and graph-transformational multi-agent systems [23] have been introduced, there is fewer research which explicitly considers the special case of adverse conditions, e.g., [9,18]. Adverse conditions are modeled by an interfering environment.…”
Section: Introductionmentioning
confidence: 99%
“…多 Agent 系统是分布式人工智能的重要研究内容 [11] .在多 Agent 系统中,Agent 群体通过个体的自主计算及 个体间的交互实现系统预定的全局目标.个体的自治与交互是多 Agent 系统的重要特征.在开放的问题求解环 境中,由于任务目标的开放性及求解过程的开放性,Agent 系统需要面临环境自适应及矛盾冲突等问题 [1] .相应 地,解决自适应及矛盾冲突等问题需要系统中大量的计算资源,例如,Agent 个体之间的通信资源.近年来,基于组 织的 Agent 计算有望成为多 Agent 系统求解问题的新途径 [12,13] .为了实现基于组织的多 Agent 问题求解,组织计 在基于组织的问题求解中,组织结构是重要的研究内容 [12] .组织结构定义了 Agent 个体之间的任务结构和 交互方式,任务结构定义了组织任务之间的父-子层次关系及资源约束,这是组织结构中角色关系设计的基础. 角色关系反映了组织的任务结构,并定义了承担相应角色的 Agent 个体的交互.为了体现组织结构元素的这种 相互关系,我们在文献 [4,14]中给出了组织结构的社会结构、角色指定和 Agent 协调 3 个维度的定量描述及基 于组织结构的 3 个维度将图变换方法应用于组织结构演化过程的描述方法.在文献 [4,14]…”
Section: Agent组织结构的3个维度特征unclassified