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Designing Collective Decision-making Dynamics for Multi-agent Systems with Inspiration From Honeybees

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서명/저자사항Designing Collective Decision-making Dynamics for Multi-agent Systems with Inspiration From Honeybees.
개인저자Gray, Rebecca A. L.
단체저자명Princeton University. Mechanical and Aerospace Engineering.
발행사항[S.l.]: Princeton University., 2019.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2019.
형태사항175 p.
기본자료 저록Dissertations Abstracts International 81-05B.
Dissertation Abstract International
ISBN9781687932303
학위논문주기Thesis (Ph.D.)--Princeton University, 2019.
일반주기 Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Includes supplementary digital materials.
Advisor: Leonard, Naomi E.
이용제한사항This item must not be sold to any third party vendors.
요약For many multi-agent systems, collective decision-making among alternatives is a crucial task. A group of agents may be required to collectively decide on their next action, and may face limitations on their sensing, communication and computational abilities. A swarm of honeybees choosing a new nest-site faces these challenges, and has been shown to reliably make decisions with accuracy, efficiency and adaptability. The honeybee decision-making dynamics can be modelled by a pitchfork bifurcation, a nonlinear phenomenon that is ubiquitous in animal decision-making.We describe and analyse a model for collective decision-making that possesses a pitchfork bifurcation. The model allows us to leverage the characteristics of the honeybee dynamics for application in multi-agent network systems and to extend the capabilities of our decision-making dynamics beyond those of the biological system.Using tools from nonlinear analysis, we show that our model retains some important characteristics of the honeybee decision-making dynamics, and we examine the impact of system and environmental parameters on the behaviour of the model. We derive an extension to an existing centrality measure to describe the relative influence of each agent, and to show how agent preferences can lead to bias in the network. We design decentralised, adaptive feedback dynamics on a parameter of the model, which ensure that a decision is made. We discuss how this system parameter, which quantifies how much each agent is influenced by its neighbours, provides an intuitive mechanism to involve a human operator in the decision-making. We continue this discussion as we implement our model with a simple robotic system.Throughout this thesis, we discuss the trade-off in the design of decision-making dynamics between systems that are robust to unwanted disturbances, but are also sensitive to the values of important system parameters. We show how dynamics modelled by a pitchfork bifurcation exhibit hypersensitivity close to the bifurcation point, and hyperrobustness far away from it.
일반주제명Mechanical engineering.
Electrical engineering.
Robotics.
언어영어
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