Abstract
This thesis explores the potential of self-regulation in collective decision making to align interests and optimise joint performance. Demonstrated in the domain of road maintenance planning, this research contributes novel incentive mechanisms and algorithmic techniques to incite self-regulation and coordinate agent interactions, paired with a practical validation of the concept through serious gaming. The learnings of this work guide the design and implementation of future performance-based partnerships and advance the current state-of-the-art in sequential decision
making.
making.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Thesis sponsors | |
Award date | 20 Nov 2020 |
Publisher | |
Print ISBNs | 978-90-5584-274-2 |
DOIs | |
Publication status | Published - 2020 |
Bibliographical note
TRAIL Thesis Series no. T2020/17, the Netherlands TRAIL Research SchoolKeywords
- Self-regulation
- Decision-theoretic planning under uncertainty
- Dynamic mechanism design
- Serious gaming