Decentralized and dynamic group formation of reconfigurable agents

Moritz, Ruby L. V.; Middendorf, Martin

doi:10.1007/s12293-014-0149-3

Cited by 4 publications

(3 citation statements)

References 17 publications

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Section: Modelmentioning

confidence: 99%

“…A slightly similar multi-agent model where the agent have to solve a resource collection task has been studied in [8,9]. However, different from this study, the agents in [8,9] have no multi-criteria decision problem, there exists no inheritance mechanisms, and the agents have different capabilities. The focus of these papers was to study different strategies for the agents to form teams in a static [8] dynamic [9] environment and limited energy conditions.…”

Section: Modelmentioning

confidence: 99%

See 1 more Smart Citation

Evolutionary Inheritance Mechanisms for Multi-criteriaDecision Making in Multi-agent Systems

Moritz

Middendorf

2015

Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

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In this paper we study the use of different evolutionary inheritance mechanisms for the adaptation of parameters in a multi-agent system where the agents have to solve tasks that are distributed within a dynamic environment. In the studied system the agents have to form teams to execute the tasks. Deciding which task to execute next is a multicriteria decision problem for which the agents use different ranking schemes. Agents that have successfully executed several tasks can reproduce and pass the type of ranking scheme they have used and some corresponding parameter values to their successors. Three types of evolutionary mechanisms are compared: haploid, diploid, and haplo-diploid. The latter one is new for multi-agent systems. The focus of our simulation experiments is to study the influence of the different evolutionary mechanisms on the diversity of the agents and on the resulting efficiency of the multi-agent system for different dynamic environments.

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Section: Modelmentioning

confidence: 99%

Section: Modelmentioning

confidence: 99%

Evolutionary Inheritance Mechanisms for Multi-criteriaDecision Making in Multi-agent Systems

Moritz

Middendorf

2015

Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

Self Cite

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“…The famous biologist Clinton Richard Dawkins (1976) first proposed the concept of Meme (translation for cultural genes) in his book "The Selfish Gene" and consider Meme is an unit of cultural transmission to explain the evolution concept of cultural [1]. Since Meme has been proposed, scholars have turned their focus on the research in Memetics: Moritz, E (1990) consider a unit that can spread culture could be called a Meme [2]; Lynch, A. (1998) consider Meme as a memory item for the storage of information within the brain; Speel, H. C.(1988) made an important supplement for Dawkins 's theory and consider Meme to be not only replicator but also intermediary of DNA [3]; Dawkins's student, Susan Blackmore (2000), made a further explanation of Meme in his book "The Meme Machine" [4].…”

Section: Introductionmentioning

confidence: 99%

Life-Cycle Low-Carbon Neighborhood: A Genetic Perspective in China

Zhao

Wang

2016

AMM

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In the end of the 19th century, the concept of greenhouse effect has drawn greater attention and scientists begin to consider climate change as a potentially serious problem. The World Economic Forum’s Global Risks Report 2016 has considered the failure of climate change mitigation and adaptation as the greatest potential risk of 2016. To cope with climate change, scholars agree that low carbon is the inevitable choice of global development and urban neighborhood, as the basic functional unit of a city, is the basic space to achieve low carbon. Along with rapid economic growth, carbon emissions in China have being increasing which accompanied with another urban problem: the recession in old city, so we put neighborhood low-carbon renewal as an effective way to promoting sustainability. Along with the rapid development of life sciences, scholars have shown great interest in cross-over study with it while gene theory plays a crucial role and has been obtained significant results over the years. In this paper, we comprehensively analyzed the achievement in cross-over study between building sciences and life sciences and introduced gene theory into the research of neighborhood low-carbon to provide the government a new theoretical tool.

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Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-Agent Systems

Golpayegani

Dusparić

Clarke

2019

ACM Trans. Intell. Syst. Technol.

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Agents frequently collaborate to achieve a shared goal or to accomplish a task that they cannot do alone. However, collaboration is difficult in open multi-agent systems where agents share constrained resources to achieve both individual and shared goals. In current approaches to collaboration, agents are organised into disjoint groups and social reasoning is used to capture their capabilities when selecting a qualified set of collaborators. These approaches are not useful when agents are in multiple, overlapping groups; depend on each other when using shared resources; have multiple goals to achieve simultaneously; and have to share the overall costs and benefits. In this article, agents use social reasoning to enhance their understanding of other agents’ goals and their dependencies, and self-adaptive techniques to adapt their level of self-interest in a collaborative process, with a view to contributing to lowering shared costs or increasing shared benefits. This model aims at improving the extent to which agents’ goals are met while improving shared resource usage efficiency. For example, in a public transport system where each mode of transport has limited capacity, commuters will be enabled to make choices that avoid over-capacity in different modes, or in a smart energy grid with limited capacity, users can make choices as to when they increase their demand. The model simultaneously helps avoid overloading a shared resource while allowing users to achieve their own goals. The proposed model is evaluated in an open multi-agent system with 100 agents operating in multiple overlapping groups and sharing multiple constrained resources. The impact of agents’ varying levels of social dependencies, mobility, and their groups’ density on their individual and shared goal achievement is analysed.

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Decentralized and dynamic group formation of reconfigurable agents

Cited by 4 publications

References 17 publications

Evolutionary Inheritance Mechanisms for Multi-criteriaDecision Making in Multi-agent Systems

Evolutionary Inheritance Mechanisms for Multi-criteriaDecision Making in Multi-agent Systems

Life-Cycle Low-Carbon Neighborhood: A Genetic Perspective in China

Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-Agent Systems

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