2014 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)
2008 - ACM Fellow For contributions to combinatorial auctions and mechanism design.
2008 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the foundations of multiagent systems and computational game theory, pioneering work in combinatorial auctions, multiagent preference elicitation, and automated mechanism design, and principles and large-scale application of electronic marketplaces.
2003 - Fellow of Alfred P. Sloan Foundation
Tuomas Sandholm mostly deals with Mathematical optimization, Combinatorial auction, Game theory, Common value auction and Multi-agent system. The various areas that Tuomas Sandholm examines in his Mathematical optimization study include Computational complexity theory and Folk theorem, Equilibrium selection. His Combinatorial auction research is multidisciplinary, incorporating elements of Proxy bid and Search algorithm.
His Game theory research includes themes of Computer security, Artificial intelligence and Operations research. His Common value auction study integrates concerns from other disciplines, such as Bidding and Mathematical economics. The concepts of his Multi-agent system study are interwoven with issues in Key and Anytime algorithm.
Tuomas Sandholm focuses on Mathematical optimization, Common value auction, Nash equilibrium, Mathematical economics and Combinatorial auction. The study incorporates disciplines such as Time complexity, Extensive-form game, Multi-agent system, Regret and Game theory in addition to Mathematical optimization. Tuomas Sandholm has researched Game theory in several fields, including Perfect information, Artificial intelligence and Operations research.
Tuomas Sandholm combines topics linked to Bidding with his work on Common value auction. His research in Nash equilibrium intersects with topics in Correlated equilibrium and Game tree. His Combinatorial auction research incorporates themes from Search algorithm and Mechanism design.
Tuomas Sandholm mainly investigates Mathematical optimization, Nash equilibrium, Extensive-form game, Game tree and Regret. Tuomas Sandholm combines subjects such as Rate of convergence, Regret minimization and Pruning with his study of Mathematical optimization. Tuomas Sandholm interconnects Correlated equilibrium, Applied mathematics, Information set and Repeated game in the investigation of issues within Nash equilibrium.
Game theory covers he research in Repeated game. His work carried out in the field of Extensive-form game brings together such families of science as State, Entropy, Algorithm and Solution concept. His Game tree research also works with subjects such as
His primary areas of study are Mathematical optimization, Game tree, Perfect information, Extensive-form game and Set. His research on Mathematical optimization focuses in particular on Nash equilibrium. His research investigates the link between Game tree and topics such as Iterative method that cross with problems in Binary entropy function, Rate of convergence, Smoothing, Equilibrium finding and Artificial intelligence.
His study in Perfect information is interdisciplinary in nature, drawing from both Chess endgame, Subgame, Theoretical computer science and Key. His study looks at the relationship between Theoretical computer science and fields such as Economic model, as well as how they intersect with chemical problems. His Set research is multidisciplinary, incorporating perspectives in Quality, Integer programming and Search algorithm.
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.
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence (2002)
Coalition structure generation with worst case guarantees
Tuomas Sandholm;Kate Larson;Martin Andersson;Onn Shehory.
Artificial Intelligence (1999)
Distributed rational decision making
Tuomas W. Sandholm.
Multiagent systems (1999)
An implementation of the contract net protocol based on marginal cost calculations
national conference on artificial intelligence (1993)
Coalitions among computationally bounded agents
Tuomas W. Sandholm;Victor R. Lesser.
Artificial Intelligence (1997)
Issues in automated negotiation and electronic commerce: extending the contract net framework
Tuomas Sandholm;Victor Lesser.
An algorithm for optimal winner determination in combinatorial auctions
international joint conference on artificial intelligence (1999)
When are elections with few candidates hard to manipulate
Vincent Conitzer;Tuomas Sandholm;Jérôme Lang.
Journal of the ACM (2007)
Computing the optimal strategy to commit to
Vincent Conitzer;Tuomas Sandholm.
electronic commerce (2006)
CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions
Tuomas Sandholm;Subhash Suri;Andrew Gilpin;David Levine.
Management Science (2005)
Profile was last updated on December 6th, 2021.
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