Publikacje

Czasopismo: JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

2023

• Oskar Skibski , Complexity of Computing the Shapley Value in Partition Function Form Games, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 77 2023, s. 1237-1274. Zobacz w PBN

2018

• Marek Cygan , Łukasz Kowalik , Arkadiusz Socała, Krzysztof Sornat, Approximation and Parameterized Complexity of Minimax Approval Voting, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 63 2018, s. 495 - 513. Zobacz w PBN
• Oskar Skibski , Tomasz Michalak , Talal Rahwan, Axiomatic Characterization of Game-Theoretic Centrality, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 62 2018, s. 33-68. Zobacz w PBN
• Mateusz Tarkowski, Piotr Szczepański, Tomasz Michalak , Paul Harrenstein, Michael Wooldridge, Efficient Computation of Semivalues for Game-Theoretic Network Centrality, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 63 2018, s. 145 - 189. Zobacz w PBN

2017

• Piotr Faliszewski, Piotr Skowron , Chamberlin-Courant Rule with Approval Ballots: Approximating the MaxCover Problem with Bounded Frequencies in FPT Time, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2017. Zobacz w PBN

2013

• Tomasz Michalak , Karthik Aadithya, Nicholas Jennings, Balaraman Ravindran, Piotr Szczepański, Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality, JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 46 2013, s. 607-650. Zobacz w PBN