D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 59 Citations 11,209 229 World Ranking 1123 National Ranking 459

Research.com Recognitions

Awards & Achievements

2019 - ACM Fellow For contributions to game theory, social choice theory, and mechanism design

2019 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the advancement of artificial intelligence through integration with economics and philosophy, including game theory, mechanism design, social choice, and ethics.

2015 - Fellow of John Simon Guggenheim Memorial Foundation

2008 - Fellow of Alfred P. Sloan Foundation

Overview

What is he best known for?

The fields of study Vincent Conitzer is best known for:

  • Game theory
  • Nash equilibrium
  • Approval voting

His study explores the link between Computational complexity theory and topics such as Algorithm that cross with problems in Computation. In his articles, he combines various disciplines, including Computation and Algorithm. His research on Epistemology often connects related areas such as Mechanism (biology) and Property (philosophy). His Mechanism (biology) study often links to related topics such as Epistemology. His work in Quantum mechanics incorporates the disciplines of Observable and Action (physics). With his scientific publications, his incorporates both Action (physics) and Quantum mechanics. Marketing is connected with Price discrimination and Advertising in his study. He integrates Advertising with Marketing in his research. In his works, he undertakes multidisciplinary study on Mathematical economics and Econometrics.

His most cited work include:

  • When are elections with few candidates hard to manipulate? (340 citations)
  • Handbook of Computational Social Choice (178 citations)
  • AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents (169 citations)

What are the main themes of his work throughout his whole career to date

As a member of one scientific family, Vincent Conitzer mostly works in the field of Game theory, focusing on Mathematical economics and, on occasion, Nash equilibrium. Algorithm overlaps with fields such as Mathematical optimization and Artificial intelligence in his research. He undertakes multidisciplinary investigations into Mathematical optimization and Mathematical economics in his work. His multidisciplinary approach integrates Artificial intelligence and Algorithm in his work. Many of his studies on Law involve topics that are commonly interrelated, such as Approval voting. His Politics research extends to Approval voting, which is thematically connected. Vincent Conitzer merges Politics with Voting in his research. Vincent Conitzer combines Voting and Cardinal voting systems in his research. His work in Cardinal voting systems is not limited to one particular discipline; it also encompasses Law.

Vincent Conitzer most often published in these fields:

  • Mathematical economics (65.28%)
  • Law (43.06%)
  • Politics (36.11%)

What were the highlights of his more recent work (between 2019-2022)?

  • Artificial intelligence (100.00%)
  • Epistemology (66.67%)
  • Algorithm (33.33%)

In recent works Vincent Conitzer was focusing on the following fields of study:

Many of his studies involve connections with topics such as Quality (philosophy) and Philosophy of science and Epistemology. His Quality (philosophy) study frequently draws connections between adjacent fields such as Epistemology. Much of his study explores Engineering ethics relationship to Ethical decision and Information ethics. Ethical decision and Engineering ethics are commonly linked in his work. Vincent Conitzer conducted interdisciplinary study in his works that combined Artificial intelligence and Algorithm. Borrowing concepts from Artificial intelligence, he weaves in ideas under Algorithm. His research ties Selection (genetic algorithm) and Machine learning together. Selection (genetic algorithm) and Machine learning are frequently intertwined in his study. Many of his studies involve connections with topics such as Market economy and Paternalism.

Between 2019 and 2022, his most popular works were:

  • Adapting a kidney exchange algorithm to align with human values (33 citations)
  • Interpretable, not black-box, artificial intelligence should be used for embryo selection (13 citations)
  • Computational ethics (7 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

When are elections with few candidates hard to manipulate

Vincent Conitzer;Tuomas Sandholm;Jérôme Lang.
Journal of the ACM (2007)

521 Citations

Computing the optimal strategy to commit to

Vincent Conitzer;Tuomas Sandholm.
electronic commerce (2006)

510 Citations

Handbook of Computational Social Choice

Felix Brandt;Vincent Conitzer;Ulle Endriss;Jérôme Lang;Jérôme Lang.
Research Papers in Economics (2016)

504 Citations

New complexity results about Nash equilibria

Vincent Conitzer;Tuomas W Sandholm.
Games and Economic Behavior (2008)

405 Citations

Complexity of mechanism design

Vincent Conitzer;Tuomas Sandholm.
uncertainty in artificial intelligence (2002)

335 Citations

Complexity results about Nash equilibria

Vincent Conitzer;Tüomas Sandholm.
international joint conference on artificial intelligence (2003)

310 Citations

Stackelberg vs. Nash in security games: an extended investigation of interchangeability, equivalence, and uniqueness

Dmytro Korzhyk;Zhengyu Yin;Christopher Kiekintveld;Vincent Conitzer.
(2011)

294 Citations

AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents

Vincent Conitzer;Tuomas Sandholm.
Machine Learning (2007)

253 Citations

Determining possible and necessary winners under common voting rules given partial orders

Lirong Xia;Vincent Conitzer.
Journal of Artificial Intelligence Research (2011)

234 Citations

A double oracle algorithm for zero-sum security games on graphs

Manish Jain;Dmytro Korzhyk;Ondřej Vaněk;Vincent Conitzer.
(2011)

212 Citations

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