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Thesis

Combined Decision Making with Multiple Agents

Alternative title:
D.Phil Thesis
Abstract:

In a wide range of applications, decisions must be made by combining information from multiple agents with varying levels of trust and expertise. For example, citizen science involves large numbers of human volunteers with differing skills, while disaster management requires aggregating information from multiple people and devices to make timely decisions. This thesis introduces efficient and scalable Bayesian inference for decision combination, allowing us to fuse the responses of multipl...

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Research group:
Machine Learning Research Group
Oxford college:
Hertford College
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK

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