Kyushu University Academic Staff Educational and Research Activities Database
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Taiki Todo Last modified date:2020.08.04

Graduate School
Undergraduate School

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 Reseacher Profiling Tool Kyushu University Pure
Academic Degree
Doctor of Informatics
Country of degree conferring institution (Overseas)
Field of Specialization
Game Theory, Multi-Agent Systems
Total Priod of education and research career in the foreign country
Research Interests
  • Applying Game Theory into Mining Software Repositories
    keyword : Game Theory, Mining Software Repositories
  • Theory for Exchange of Multiple Indivisible Goods
    keyword : Top-Trading-Cycles algorithm, exchange market, core assignments, kidney exchange
  • Effect of False-Name Manipulations in Market Design Environments
    keyword : Game Theory, Mechanism Design
Academic Activities
1. Takehiro Kawasaki, Nathanael Barrot, Seiji Takanashi, Taiki Todo, and Makoto Yokoo, Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network, The 34th AAAI Conference on Artificial Intelligence (AAAI-2020), 2020.02, Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naı̈ve ones. In this paper, we first propose a mechanism that satisfies all the above properties. We then make a comprehensive comparison with two naı̈ve mechanisms, showing that the proposed mechanism dominates them in social surplus, seller’s revenue, and incentive of buyers for truth-telling. We also analyze the characteristics of the social surplus and the revenue achieved by the proposed mechanism, including the constant approximability of the worst-case efficiency loss and the complexity of optimizing revenue from the seller’s perspective..
2. Etsushi Fujita, Julien Lesca, Akihisa Sonoda, Taiki Todo, Makoto Yokoo, A complexity approach for core-selecting exchange under conditionally lexicographic preferences, Journal of Artificial Intelligence Research, 10.1613/jair.1.11254, 63, 515-555, 2018.11, Core-selection is a crucial property of rules in the literature of resource allocation. It is also desirable, from the perspective of mechanism design, to address the incentive of agents to cheat by misreporting their preferences. this paper investigates the exchange problem where (i) each agent is initially endowed with (possibly multiple) indivisible goods, (ii) agents' preferences are assumed to be conditionally lexicographic, and (iii) side payments are prohibited. We propose an exchange rule called augmented top-trading-cycles (ATTC), based on the original TTC procedure. We first show that ATTC is core-selecting and runs in polynomial time with respect to the number of goods. We then show that finding a beneficial misreport under ATTC is NP-hard. We finally clarify relationship of misreporting with splitting and hiding, two different types of manipulations, under ATTC..
1. Taiki Todo, Market Design with Uncertainty, IJCAI-PRICAI-20, 2021.01.
2. Etsushi Fujita, Julien Lesca, Akihisa Sonoda, Taiki Todo, Makoto Yokoo, A Complexity Approach for Core-Selecting Exchange with Multiple Indivisible Goods under Lexicographic Preferences, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), 2015.01.
Membership in Academic Society
  • Association for Computing Machinery (ACM)
  • Association for the Advancement of Artificial Intelligence (AAAI)
  • Japan Society for Software Science and Technology
  • The Japanese Society for Artificial Intelligence
  • Information Processing Society of Japan