What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Statistics
His main research concerns Mathematical optimization, Distributed computing, Constraint satisfaction problem, Constraint satisfaction and Backtracking.
His research in Mathematical optimization intersects with topics in Hybrid algorithm, Combinatorial auction, Mathematical economics, Partially observable Markov decision process and Multi-agent system.
His Distributed computing research includes elements of Control, Server, Asynchronous communication and Public-key cryptography.
The Constraint satisfaction problem study combines topics in areas such as Distributed algorithm, Theoretical computer science and Search algorithm.
While the research belongs to areas of Constraint satisfaction, Makoto Yokoo spends his time largely on the problem of Algorithm, intersecting his research to questions surrounding AC-3 algorithm.
He has researched Backtracking in several fields, including Constraint satisfaction dual problem, Constraint learning and Distributed constraint optimization.
His most cited work include:
- Adopt: asynchronous distributed constraint optimization with quality guarantees (672 citations)
- The distributed constraint satisfaction problem: formalization and algorithms (619 citations)
- Algorithms for Distributed Constraint Satisfaction: A Review (354 citations)
What are the main themes of his work throughout his whole career to date?
Makoto Yokoo spends much of his time researching Mathematical optimization, Mathematical economics, Common value auction, Combinatorial auction and Theoretical computer science.
The study incorporates disciplines such as Matching, Multi-agent system, Distributed constraint optimization, Algorithm and Constraint satisfaction problem in addition to Mathematical optimization.
His studies in Multi-agent system integrate themes in fields like Quality and Distributed computing.
The various areas that Makoto Yokoo examines in his Constraint satisfaction problem study include Constraint satisfaction and Backtracking.
His Common value auction study combines topics in areas such as Bidding, The Internet and Mechanism design.
His research investigates the connection between Combinatorial auction and topics such as Vickrey–Clarke–Groves auction that intersect with problems in Incentive compatibility.
He most often published in these fields:
- Mathematical optimization (40.35%)
- Mathematical economics (14.11%)
- Common value auction (13.86%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (40.35%)
- Matching (8.17%)
- Microeconomics (7.67%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Mathematical optimization, Matching, Microeconomics, Mathematical economics and Theoretical computer science.
His Mathematical optimization study incorporates themes from Function, Class, Constraint satisfaction problem and Distributed constraint optimization problem.
In his study, which falls under the umbrella issue of Constraint satisfaction problem, Computation is strongly linked to State.
The concepts of his Distributed constraint optimization problem study are interwoven with issues in Algorithm and Distributed constraint optimization.
His Mathematical economics research is multidisciplinary, incorporating perspectives in Simulation and Combinatorial auction.
His work deals with themes such as Facility location problem, Representation, Time complexity and Decision tree, which intersect with Theoretical computer science.
Between 2015 and 2021, his most popular works were:
- Strategyproof Matching with Minimum Quotas (62 citations)
- Strategyproof matching with regional minimum and maximum quotas (31 citations)
- Designing matching mechanisms under constraints: An approach from discrete convex analysis (30 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Statistics
Makoto Yokoo mainly investigates Mathematical optimization, Matching, Mathematical economics, Time complexity and Strategyproof.
Makoto Yokoo undertakes multidisciplinary studies into Mathematical optimization and Context in his work.
His Matching research incorporates themes from Stability and Pareto principle.
His work on Envy-free as part of general Mathematical economics study is frequently linked to Property, Cardinal voting systems and Extension, therefore connecting diverse disciplines of science.
His studies deal with areas such as Theoretical computer science, Measure, Core, Graph and Node as well as Time complexity.
His Strategyproof study integrates concerns from other disciplines, such as Parameterized complexity and Minimax.
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