TY - GEN
T1 - Mechanism design with uncertainty
AU - Todo, Taiki
N1 - Funding Information:
This work was partially supported by JSPS Kakenhi Grant Numbers JP17H04695 and JP20H00587. The author thanks all the co-authors, collaborators, and discussants.
PY - 2020
Y1 - 2020
N2 - My research is summarized as mechanism design with uncertainty. Traditional mechanism design focuses on static environments where all the (possibly probabilistic) information about the agents are observable by the mechanism designer. In practice, however, it is possible that the set of participating agents and/or some of their actions are not observable a priori. We therefore focused on various kinds of uncertainty in mechanism design and developed/analyzed several market mechanisms that incentivise agents to behave in a sincere way.
AB - My research is summarized as mechanism design with uncertainty. Traditional mechanism design focuses on static environments where all the (possibly probabilistic) information about the agents are observable by the mechanism designer. In practice, however, it is possible that the set of participating agents and/or some of their actions are not observable a priori. We therefore focused on various kinds of uncertainty in mechanism design and developed/analyzed several market mechanisms that incentivise agents to behave in a sincere way.
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UR - http://www.scopus.com/inward/citedby.url?scp=85097336254&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85097336254
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 5174
EP - 5177
BT - Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020
A2 - Bessiere, Christian
PB - International Joint Conferences on Artificial Intelligence
T2 - 29th International Joint Conference on Artificial Intelligence, IJCAI 2020
Y2 - 1 January 2021
ER -