Atari games | Synced

by Synced 2022-09-21 126

DeepMind’s MEME Agent Achieves Human-level Atari Game Performance 200x Faster Than Agent57

In the new paper Human-level Atari 200x Faster, a DeepMind research team applies a set of diverse strategies to Agent57, with their resulting MEME (Efficient Memory-based Exploration) agent surpassing the human baseline on all 57 Atari games in just 390 million frames — two orders of magnitude faster than Agent57.

by Synced 2021-06-29 2

AI Machine Learning & Data Science Research

DeepMind & Amii Extend Emphatic Algorithms for Deep RL, Improving Performance on Atari Games

A research team from DeepMind and Amii extends the emphatic method to multi-step deep reinforcement learning (RL) targets, and demonstrates that combining emphatic trace with deep neural networks can improve performance on classic Atari video games.

by Synced 2020-04-01 1

AI Machine Learning & Data Science Research

Google DeepMind ‘Agent 57’ Beats Human Baselines Across Atari Games Suite

Agent57 is the first deep reinforcement learning (RL) agent to top human baseline scores on all games in the Atari57 test set.

by Synced 2019-03-19 0

AI Interview Research

Google Brain SimPLe: Complete Model-Based Reinforcement Learning for Atari

Model-free reinforcement learning can be used to learn effective strategies for complex tasks such as Atari games, but it usually requires a large amount of interaction, which adds significant time and cost.