most citedBounds for Approximate Regret-Matching Algorithms

3 citations · 4 across the 3 of their papers we have counts for

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cs.AI2021

Solving Common-Payoff Games with Approximate Policy Iteration

Samuel Sokota, Edward Lockhart, Finbarr Timbers +6

For artificially intelligent learning systems to have widespread applicability in real-world settings, it is important that they be able to operate decentrally. Unfortunately, dece…

cs.AI2019

Alternative Function Approximation Parameterizations for Solving Games: An Analysis of -Regression Counterfactual Regret Minimization

Ryan D'Orazio, Dustin Morrill, James R. Wright +1

Function approximation is a powerful approach for structuring large decision problems that has facilitated great achievements in the areas of reinforcement learning and game playin…