26 citations · 50 across the 19 of their papers we have counts for
22 papers
What You Earn from What You Learn: Characterization and Complexity of the Value of Information
Ratip Emin Berker, Ioannis Anagnostides, Emanuel Tewolde +3
We examine the value of information in extensive-form decision problems: the largest multiplicative gain that a decision maker can obtain from an information refinement, taken over…
Normal-Form Correlation in Markov Games
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina +3
There has been a surge of recent work on correlated equilibrium concepts in Markov games. However, existing results focus on concepts weaker than normal-form correlated equilibria…
Polynomial-time computation of -contraction fixed points for even
Constantinos Daskalakis, Gabriele Farina, Brian Hu Zhang
We give a -time algorithm that computes an -approximate fixed point of any -nonexpansive map , where $\mat…
On the Complexity of Correlated Equilibria Beyond Normal-Form Games
Ioannis Anagnostides, Constantinos Daskalakis, Gabriele Farina +3
Correlated equilibria are a fundamental solution concept in game theory. However, despite decades of research, the complexity beyond games of polynomial type -- such as extensive-f…
Imperfect-Recall Games: Equilibrium Concepts and Their Complexity
Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld +4
We investigate optimal decision making under imperfect recall, that is, when an agent forgets information it once held before. An example is the absentminded driver game, as well a…
A Lower Bound on Swap Regret in Extensive-Form Games
Constantinos Daskalakis, Gabriele Farina, Noah Golowich +2
Recent simultaneous works by Peng and Rubinstein [2024] and Dagan et al. [2024] have demonstrated the existence of a no-swap-regret learning algorithm that can reach average sw…