RT @eugenevinitsky

“So much of research effectiveness is just good emotional regulation:
- ignoring the deluge of papers and continuing to read despite analysis paralysis
- finding motivation to work even though the amount of work is technically infinite”

This really resonates with me. Also, finding a balance of: standing up for your work and analysis, but having the emotional maturity to listen to and accept criticisms, to see the truth in them, and improve the next time.

#introduction

I am a scientist at Meta AI in NYC and study machine learning and optimization, recently involving reinforcement learning, control, optimal transport, and geometry. On social media, I enjoy finding and boosting interesting content from the original authors on these topics

I made this small animation with my recent project on optimal transport that connects continuous structures in the world. The source code to reproduce this and other examples is online at https://github.com/facebookresearch/w2ot

[https://twitter.com/michaeld1729/status/1604855967879172096?s=46&t=wxGlb03ZPSMgGiSpSUli_g | XP]
Very interesting result, showing that one can do very well on the very popular SMAC benchmark without looking at the observations!

This should be a reminder that progress in RL and MARL is hard to measure well, and even when progress is being made by a well defined metric, it is often not for the reasons we think!

#MARL #RL #reinforcementlearning