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Takamasa Suzuki

dblp:180/1437 · DBLP profile ↗
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5ranked-venue papers
1as first author
2since 2021 · last 2023
0000-0003-3030-6599ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 1 first-author · 2 since 2021Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
3 papers
Algorithmic game theory and mechanism design · 83% Graph algorithms and graph theory · 17%

Topics — the 7 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
coalitional game
0.612022
Measuring power in coalitional games with friends, enemies and allies · Artif. Intell. 2022
Algorithmic game theory and mechanism design › social choice › voting power
power index
0.612022
Measuring power in coalitional games with friends, enemies and allies · Artif. Intell. 2022
Graph algorithms and graph theory › graph classes
signed graph
0.612022
Measuring power in coalitional games with friends, enemies and allies · Artif. Intell. 2022
Algorithmic game theory and mechanism design › market design
matching markets
0.312017
Strategy-proof school choice mechanisms with minimum quotas and initial endowments · Artif. Intell. 2017
Algorithmic game theory and mechanism design › market design › matching markets
school choice
0.312017
Strategy-proof school choice mechanisms with minimum quotas and initial endowments · Artif. Intell. 2017
Algorithmic game theory and mechanism design › mechanism design
truthful mechanism
0.312017
Strategy-proof school choice mechanisms with minimum quotas and initial endowments · Artif. Intell. 2017
Algorithmic game theory and mechanism design
matching
0.212023
Strategyproof Allocation Mechanisms with Endowments and M-convex Distributional Constraints · Artif. Intell. 2023

Methods — techniques the papers use, named apart from their topics

top-trading-cycles · 0.9pseudo-polynomial algorithm · 0.6axiomatic approach · 0.6deferred acceptance · 0.3
YearPublicationVenuePosition
2023 Strategyproof Allocation Mechanisms with Endowments and M-convex Distributional Constraints
abstract
We consider an allocation problem of multiple types of objects to agents, where each type of object has multiple copies (e.g., multiple seats in a school), each agent is endowed with an object, and some distributional constraints are imposed on the allocation (e.g., minimum/maximum quotas). We develop two mechanisms that are strategyproof, feasible (they always satisfy distributional constraints), and individually rational, assuming the distributional constraints are represented by an M-convex set. One mechanism, based on Top Trading Cycles, is Pareto efficient; the other, which belongs to the mechanism class specified by Kojima et al. [1], satisfies a relaxed fairness requirement. The class of distributional constraints we consider contains many situations raised from realistic matching problems, including individual minimum/maximum quotas, regional maximum quotas, type-specific quotas, and distance constraints. Finally, we experimentally evaluate the performance of these mechanisms by a computer simulation.
Takamasa Suzuki, Akihisa Tamura, Kentaro Yahiro, Makoto Yokoo, Yuzhe Zhang 0001
Artif. Intell.1
2022 Measuring power in coalitional games with friends, enemies and allies
abstract
We extend the well-known model of graph-restricted games due to Myerson to signed graphs. In our model, it is possible to explicitly define not only that some players are friends (as in Myerson's model) but also that some other players are enemies. As such our games can express a wider range of situations, e.g., animosities between political parties. We define the value for signed graph games using the axiomatic approach that closely follows the celebrated characterization of the Myerson value. Furthermore, we propose an algorithm for computing an arbitrary semivalue, including the extension of the Myerson value proposed by us. We also develop a pseudo-polynomial algorithm for power indices in weighted voting games for signed graphs with bounded treewidth. Moreover, we consider signed graph games with a priori defined alliances (unions) between players and propose algorithms to compute the extension of the Owen value to this setting.
Oskar Skibski, Takamasa Suzuki, Tomasz Grabowski, Yuko Sakurai, Tomasz P. Michalak, Makoto Yokoo
Artif. Intell.2
2019 Weighted Matching Markets with Budget Constraints
abstract
We investigate markets with a set of students on one side and a set of colleges on the other. A student and college can be linked by a weighted contract that defines the student's wage, while a college's budget for hiring students is limited. Stability is a crucial requirement for matching mechanisms to be applied in the real world. A standard stability requirement is coalitional stability, i.e., no pair of a college and group of students has any incentive to deviate. We find that a coalitionally stable matching is not guaranteed to exist, verifying the coalitional stability for a given matching is coNP-complete, and the problem of finding whether a coalitionally stable matching exists in a given market, is SigmaP2-complete: NPNP-complete. Other negative results also hold when blocking coalitions contain at most two students and one college. Given these computational hardness results, we pursue a weaker stability requirement called pairwise stability, where no pair of a college and single student has an incentive to deviate. Unfortunately, a pairwise stable matching is not guaranteed to exist either. Thus, we consider a restricted market called a typed weighted market, in which students are partitioned into types that induce their possible wages. We then design a strategy-proof and Pareto efficient mechanism that works in polynomial-time for computing a pairwise stable matching in typed weighted markets.
Anisse Ismaili, Naoto Hamada, Yuzhe Zhang 0001, Takamasa Suzuki, Makoto Yokoo
J. Artif. Intell. Res.4
2017 Strategy-proof school choice mechanisms with minimum quotas and initial endowments
abstract
We consider a school choice program where minimum quotas are imposed for each school, i.e., a school must be assigned at least a certain number of students to operate. We require that the obtained matching must respect the initial endowments, i.e., each student must be assigned to a school that is at least as good as her initial endowment school. Although minimum quotas are relevant in school choice programs and strategy-proofness is important to many policymakers, few existing mechanisms simultaneously achieve both. One difficulty is that no strategy-proof mechanism exists that is both efficient and fair under the presence of minimum quotas. Furthermore, existing mechanisms require that all students consider all schools acceptable to obtain a feasible matching that respects minimum quotas. This assumption is unrealistic in a school choice program. We consider the environment where a student considers her initial endowment school acceptable and the initial endowments satisfy all the minimum quotas. We develop two strategy-proof mechanisms. One mechanism, which we call the Top Trading Cycles among Representatives with Supplementary Seats (TTCR-SS), is based on the Top Trading Cycles (TTC) mechanism and is significantly extended to handle the supplementary seats of schools while respecting minimum quotas. TTCR-SS is Pareto efficient. The other mechanism, which we call Priority List-based Deferred Acceptance with Minimum Quotas (PLDA-MQ), is based on the Deferred Acceptance (DA) mechanism. PLDA-MQ is fair, satisfies a concept called Priority List-based (PL-) stability, and obtains the student-optimal matching within all PL-stable matchings. Our simulation results show that our new mechanisms are significantly better than simple extensions of the existing mechanisms.
Naoto Hamada, Chia-Ling Hsu, Ryoji Kurata, Takamasa Suzuki, Suguru Ueda, Makoto Yokoo
Artif. Intell.4
2017 Cooperative games with restricted formation of coalitions
Gleb A. Koshevoy, Takamasa Suzuki, Dolf Talman
Discret. Appl. Math.2