Dustin Morrill | DeepAI

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∙ 06/04/2022

Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration

Neural replicator dynamics (NeuRD) is an alternative to the foundational...

1 Dustin Morrill, et al. ∙

∙ 05/24/2022

Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games: Corrections

Hindsight rationality is an approach to playing general-sum games that p...

5 Dustin Morrill, et al. ∙

∙ 11/15/2021

The Partially Observable History Process

We introduce the partially observable history process (POHP) formalism f...

4 Dustin Morrill, et al. ∙

∙ 10/29/2021

Learning to Be Cautious

A key challenge in the field of reinforcement learning is to develop age...

8 Montaser Mohammedalamen, et al. ∙

∙ 02/13/2021

Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games

Hindsight rationality is an approach to playing multi-agent, general-sum...

4 Dustin Morrill, et al. ∙

∙ 12/10/2020

Hindsight and Sequential Rationality of Correlated Play

Driven by recent successes in two-player, zero-sum game solving and play...

1 Dustin Morrill, et al. ∙

∙ 08/27/2020

The Advantage Regret-Matching Actor-Critic

Regret minimization has played a key role in online learning, equilibriu...

0 Audrūnas Gruslys, et al. ∙

∙ 12/06/2019

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

Function approximation is a powerful approach for structuring large deci...

0 Ryan D'Orazio, et al. ∙

∙ 10/03/2019

Bounds for Approximate Regret-Matching Algorithms

A dominant approach to solving large imperfect-information games is Coun...

0 Ryan D'Orazio, et al. ∙

∙ 08/26/2019

OpenSpiel: A Framework for Reinforcement Learning in Games

OpenSpiel is a collection of environments and algorithms for research in...

12 Marc Lanctot, et al. ∙

∙ 06/01/2019

Neural Replicator Dynamics

In multiagent learning, agents interact in inherently nonstationary envi...

12 Shayegan Omidshafiei, et al. ∙

∙ 03/13/2019

Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent

In this paper, we present exploitability descent, a new algorithm to com...

20 Edward Lockhart, et al. ∙

∙ 01/06/2017

DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker

Artificial intelligence has seen several breakthroughs in recent years, ...

0 Matej Moravčík, et al. ∙

∙ 11/28/2014

Solving Games with Functional Regret Estimation

We propose a novel online learning method for minimizing regret in large...

0 Kevin Waugh, et al. ∙

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