Self-Organizing Multi-Agent Systems

C.J. van Leeuwen

doi:10.4233/uuid:face1276-5025-4853-996a-30d6771cf24d

Self-Organizing Multi-Agent Systems

C.J. van Leeuwen

Embedded Systems

Research output: Thesis › Dissertation (TU Delft)

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Abstract

In this thesis I research the ability of groups of agents to organize their collective behavior, without any human intervention. Using a framework for gathering information of the behavior, analyzing the performance, and updating the behavior, the agents can adapt to changing environments or user requirements. In my thesis I use different mechanisms driving the self-organization, but mostly focus on Distributed Constraint Optimization Problems (DCOPs) to do so. A new algorithm called CoCoA (Cooperative Constraint Approximation) is used to quickly find solutions that are near-optimal. Throughout my thesis the approach is put to use for different applications such as sensor networks, wireless power transfer networks and smart grids.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Delft University of Technology
Supervisors/Advisors	Langendoen, K.G., Supervisor Pawelczak, P., Advisor
Thesis sponsors	TNO
Award date	8 Feb 2021
Print ISBNs	978-94-6366-362-5
DOIs	https://doi.org/10.4233/uuid:face1276-5025-4853-996a-30d6771cf24d
Publication status	Published - 2021

Bibliographical note

data: https://doi.org/10.4121/13066052
code: https://doi.org/10.4121/13066028

Keywords

Self-organisation
Multi-agent systems
Artificial Intelligence (AI)
distributed optimization
Smart Grid
Wireless Power Transfer
Autonomous systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.4233/uuid:face1276-5025-4853-996a-30d6771cf24d

C.J. van Leeuwen - Self-Organizing Multi-Agent SystemsFinal published version, 1.3 MBLicence: Unspecified

SAM Experiment Results described in the PhD Thesis: Self-Organizing Multi-Agent Systems
van Leeuwen, C. (Creator), TU Delft - 4TU.ResearchData, 8 Oct 2020
DOI: 10.4121/13066052
Dataset/Software: Dataset

Cite this

@phdthesis{face127650254853996a30d6771cf24d,

title = "Self-Organizing Multi-Agent Systems",

abstract = "In this thesis I research the ability of groups of agents to organize their collective behavior, without any human intervention. Using a framework for gathering information of the behavior, analyzing the performance, and updating the behavior, the agents can adapt to changing environments or user requirements. In my thesis I use different mechanisms driving the self-organization, but mostly focus on Distributed Constraint Optimization Problems (DCOPs) to do so. A new algorithm called CoCoA (Cooperative Constraint Approximation) is used to quickly find solutions that are near-optimal. Throughout my thesis the approach is put to use for different applications such as sensor networks, wireless power transfer networks and smart grids.",

keywords = "Self-organisation, Multi-agent systems, Artificial Intelligence (AI), distributed optimization, Smart Grid, Wireless Power Transfer, Autonomous systems",

author = "{van Leeuwen}, C.J.",

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year = "2021",

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language = "English",

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PY - 2021

Y1 - 2021

N2 - In this thesis I research the ability of groups of agents to organize their collective behavior, without any human intervention. Using a framework for gathering information of the behavior, analyzing the performance, and updating the behavior, the agents can adapt to changing environments or user requirements. In my thesis I use different mechanisms driving the self-organization, but mostly focus on Distributed Constraint Optimization Problems (DCOPs) to do so. A new algorithm called CoCoA (Cooperative Constraint Approximation) is used to quickly find solutions that are near-optimal. Throughout my thesis the approach is put to use for different applications such as sensor networks, wireless power transfer networks and smart grids.

AB - In this thesis I research the ability of groups of agents to organize their collective behavior, without any human intervention. Using a framework for gathering information of the behavior, analyzing the performance, and updating the behavior, the agents can adapt to changing environments or user requirements. In my thesis I use different mechanisms driving the self-organization, but mostly focus on Distributed Constraint Optimization Problems (DCOPs) to do so. A new algorithm called CoCoA (Cooperative Constraint Approximation) is used to quickly find solutions that are near-optimal. Throughout my thesis the approach is put to use for different applications such as sensor networks, wireless power transfer networks and smart grids.

KW - Self-organisation

KW - Multi-agent systems

KW - Artificial Intelligence (AI)

KW - distributed optimization

KW - Smart Grid

KW - Wireless Power Transfer

KW - Autonomous systems

U2 - 10.4233/uuid:face1276-5025-4853-996a-30d6771cf24d

DO - 10.4233/uuid:face1276-5025-4853-996a-30d6771cf24d

M3 - Dissertation (TU Delft)

SN - 978-94-6366-362-5

ER -

Self-Organizing Multi-Agent Systems

Abstract

Bibliographical note

Keywords

UN SDGs

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Datasets

SAM Experiment Results described in the PhD Thesis: Self-Organizing Multi-Agent Systems

Cite this