Oh A LOT of resources, may have to break this down. I’m most interested in using video games for quantified self, though a lot of gaming APIs come initially from RL AIs on them
https://twitter.com/dr_cintas/status/1713988524230250772 for a lumosity game or game not easily in their database?
We’re releasing a Neural MMO, a massively multiagent game environment for reinforcement learning agents. Our platform supports a large, variable number of agents within a persistent and open-ended task. The inclusion of many agents and species...
We’re releasing the full version of Gym Retro, a platform for reinforcement learning research on games. This brings our publicly-released game count from around 70 Atari games and 30 Sega games to over 1,000 games across a variety of backing...
We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default...
Joseph Suarez has some packages + reading group
We’re releasing the public beta of OpenAI Gym, a toolkit for developing and comparing reinforcement learning (RL) algorithms. It consists of a growing suite of environments (from simulated robots to Atari games), and a site for comparing and...
01/31/23 - Recent work has shown that, in generative modeling, cross-entropy loss
improves smoothly with model size and training compute, fol...
https://twitter.com/awjuliani/status/1714006806840631412 (he will update his tutorial to use codebases way more elegant than tensorflow)
Arthur W. Juliani, PhD (awjuliani.github.io)
https://supermemo.guru/wiki/SuperMemo_Guru
