Paul Müller | DeepAI

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∙ 02/01/2023

Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning

Multiagent reinforcement learning (MARL) has benefited significantly fro...

0 Zun Li, et al. ∙

∙ 09/22/2022

Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments

The Game Theory Multi-Agent team at DeepMind studies several aspects...

3 Ian Gemp, et al. ∙

∙ 08/22/2022

Learning Correlated Equilibria in Mean-Field Games

The designs of many large-scale systems today, from traffic routing envi...

0 Paul Müller, et al. ∙

∙ 06/30/2022

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

We introduce DeepNash, an autonomous agent capable of learning to play t...

6 Julien Perolat, et al. ∙

∙ 11/16/2021

Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO

Recent advances in multiagent learning have seen the introduction ofa fa...

0 Paul Müller, et al. ∙

∙ 06/17/2021

Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers

Two-player, constant-sum games are well studied in the literature, but t...

0 Luke Marris, et al. ∙

∙ 06/08/2021

Time-series Imputation of Temporally-occluded Multiagent Trajectories

In multiagent environments, several decision-making individuals interact...

16 Shayegan Omidshafiei, et al. ∙

∙ 05/25/2021

From Motor Control to Team Play in Simulated Humanoid Football

Intelligent behaviour in the physical world exhibits structure at multip...

2 Siqi Liu, et al. ∙

∙ 11/18/2020

Game Plan: What AI can do for Football, and What Football can do for AI

The rapid progress in artificial intelligence (AI) and machine learning ...

11 Karl Tuyls, et al. ∙

∙ 05/04/2020

Navigating the Landscape of Multiplayer Games to Probe the Drosophila of AI

Multiplayer games have a long history in being used as key testbeds for ...

11 Shayegan Omidshafiei, et al. ∙

∙ 03/30/2020

The Operating System of the Neuromorphic BrainScaleS-1 System

BrainScaleS-1 is a wafer-scale mixed-signal accelerated neuromorphic sys...

0 Eric Müller, et al. ∙

∙ 09/27/2019

A Generalized Training Approach for Multiagent Learning

This paper investigates a population-based training regime based on game...

20 Paul Müller, 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. ∙

∙ 07/06/2018

Generative models on accelerated neuromorphic hardware

The traditional von Neumann computer architecture faces serious obstacle...

40 Akos F. Kungl, et al. ∙

∙ 03/21/2017

An Accelerated Analog Neuromorphic Hardware System Emulating NMDA- and Calcium-Based Non-Linear Dendrites

This paper presents an extension of the BrainScaleS accelerated analog n...

0 Johannes Schemmel, et al. ∙

∙ 03/17/2017

Pattern representation and recognition with accelerated analog neuromorphic systems

Despite being originally inspired by the central nervous system, artific...

0 Mihai A. Petrovici, et al. ∙

∙ 04/29/2014

Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms

Advancing the size and complexity of neural network models leads to an e...

0 Mihai A. Petrovici, et al. ∙

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