A Survey of Self-Organization Mechanisms in Multiagent Systems

Ye, Dayong; Zhang, Minjie; Vasilakos, Athanasios V.

doi:10.1109/tsmc.2015.2504350

Cited by 129 publications

(69 citation statements)

References 133 publications

(179 reference statements)

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“…Moreover, the negotiation logic between the customers is presented at a basic level. Successful barter transactions may require a more complex negotiation rationale [73]. In addition, the business logic in the agent plans are mostly developed as the delta codes and hence our aim is to leverage the comprehensiveness of the models.…”

Section: Resultsmentioning

confidence: 99%

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

et al. 2018

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In agent-oriented software engineering (AOSE), the application of model-driven development (MDD) and the use of domain-specific modeling languages (DSMLs) for Multi-Agent System (MAS) development are quite popular since the implementation of MAS is naturally complex, error-prone, and costly due to the autonomous and proactive properties of the agents. The internal agent behavior and the interaction within the agent organizations become even more complex and hard to implement when the requirements and interactions for the other agent environments such as the Semantic Web are considered. Hence, in this study, we propose a modeldriven MAS development methodology which is based on a domain-specific modeling language (called SEA_ML) and covers the whole process of analysis, modeling, code generation and implementation of a MAS working in the Semantic Web according to the well-known Belief-Desire-Intention (BDI) agent principles. The use of new SEA_ML-based MAS development methodology is exemplified with the development of a semantic web-enabled MAS for electronic bartering (Ebarter). Achieved results validated the generation and the development-time performance of applying this new MAS development methodology. More than half of the all agents and artifacts needed for fully implementing the E-barter MAS were automatically obtained by just using the generation features of the proposed methodology.

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Section: Resultsmentioning

confidence: 99%

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

et al. 2018

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“…The alternative approach is to introduce a self-organzing communication structure that orchestrates in a cooperative and decentralized way searching of the combinatorial space [13]. This paper studies the role of such an agents' structure in performance.…”

Section: Research Positioningmentioning

confidence: 99%

“…The distance to the origin can be calculated with the Euclidean distance between the two points (x 1 , y 1 , z 1 ) and (x 2 , y 2 , z 2 ) as (x 1 − x 2 ) 2 + (y 1 − y 2 ) 2 + (z 1 − z 2 ) 2 , where the coordinates represent the global cost for each dataset. 13 Non-parametric estimation makes no assumptions on the underlying distribution, hence it has no parameters.…”

Section: Evaluation Approach For Optimalitymentioning

confidence: 99%

Structural Self-Adaptation for Decentralized Pervasive Intelligence

Nikolic

Pournaras

2019

2019 22nd Euromicro Conference on Digital System Design (DSD)

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Communication structure plays a key role in the learning capability of decentralized systems. Structural selfadaptation, by means of self-organization, changes the order as well as the input information of the agents' collective decisionmaking. This paper studies the role of agents' repositioning on the same communication structure, i.e. a tree, as the means to expand the learning capacity in complex combinatorial optimization problems, for instance, load-balancing power demand to prevent blackouts or efficient utilization of bike sharing stations. The optimality of structural self-adaptations is rigorously studied by constructing a novel large-scale benchmark that consists of 4000 agents with synthetic and real-world data performing 4 million structural self-adaptations during which almost 320 billion learning messages are exchanged. Based on this benchmark dataset, 124 deterministic structural criteria, applied as learning meta-features, are systematically evaluated as well as two online structural self-adaptation strategies designed to expand learning capacity. Experimental evaluation identifies metrics that capture agents with influential information and their optimal positioning. Significant gain in learning performance is observed for the two strategies especially under low-performing initialization. Strikingly, the strategy that triggers structural self-adaptation in a more exploratory fashion is the most cost-effective.

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“…Theorem 1. Consider a networked system consisting of N agents with 1 actual leader, in which each agent is steered by dynamics (5) with control input (10) and the actual leader regulates itself according to Equation 8. Suppose that the communication topology satisfies Assumptions 1 and 2.…”

Section: Robust Swarm Tracking Via State-feedback Controlmentioning

confidence: 99%

“…5 Mathematical graph theory 6 is a useful tool for investigating cooperation control of multiple-agent systems, which describes the interaction relationship among the agents. Today, there is a large volume of literature on the cooperation of multiagent systems [7][8][9][10][11] and on coupled harmonic oscillators. [12][13][14][15][16][17] The objective of cooperation control is to guide all agents (or harmonic oscillators) to accomplish a coordinated task or to reach an agreement.…”

Section: Introductionmentioning

confidence: 99%

Robust semiglobal swarm tracking of coupled harmonic oscillators with input saturation and external disturbance

Wang

et al. 2017

Intl J Robust & Nonlinear

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The robust semiglobal swarm tracking problem of N coupled harmonic oscillators and 1 actual leader with input saturation and external disturbance on a directed communication topology is considered, in which the N coupled harmonic oscillators are referred to followers. First, the low-and-high gain feedback technique is introduced to construct a relative state-dependent control algorithm. Then, an observer-based control algorithm is designed based on the low-and-high gain feedback technique and the high-gain observer design methodology. Sufficient conditions are derived to guarantee robust semiglobal swarm tracking for state-feedback control and output-feedback control, respectively. Numerical simulations are finally provided to verify the theoretic results. KEYWORDS coupled harmonic oscillators, disturbance, high-gain observer, low-and-high gain feedback, swarm tracking 1566

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A Survey of Self-Organization Mechanisms in Multiagent Systems

Cited by 129 publications

References 133 publications

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

Structural Self-Adaptation for Decentralized Pervasive Intelligence

Robust semiglobal swarm tracking of coupled harmonic oscillators with input saturation and external disturbance

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