3 ms·

Anyone interested in delving into reinforcement learning should check out our book https://www.manning.com/books/deep-reinforcement-learning-in-action https://w

Anyone interested in delving into reinforcement learning should check out our book https://www.manning.com/books/deep-reinforcement-learning-in-action https://www.manning.com/books/deep-reinforcement-learning-in... - we cover actor critic (used in this paper) to multi-agent to relational/attention models

jmeister 6y ago
Thanks, looks very useful. Since you seem to be industry practitioners: I moved away from RL 10 yrs back disillusioned with lack of real-world applicability. Has that changed significantly? The only major name I’ve heard of is Vowpal Wabbit. Maybe there are more applications being done in stealth. Any insight? Thanks
- johnmoberg 6y ago
  You might be interested in the recently-launched Covariant (https://covariant.ai/ https://covariant.ai/), they apparently actually have systems in production. Pieter Abbeel is one of the founders and they have some pretty "heavy" investors, like Jeff Dean, Geoffrey Hinton, and Yann LeCun.
  - jmeister 6y ago
    Thanks! OpenAI has made some progress on this problem too: https://news.ycombinator.com/item?id=21259765 https://news.ycombinator.com/item?id=21259765 Looks like these two places are on the cusp of a major breakthrough in RL/robotics!
- outlace 6y ago
  Honestly, not much has changed. The primary use cases continue to be things like robotics, playing games, finance etc. I’m interested in RL academically from a computational neuroscience standpoint (using RL to model cognition) but also as applied toward healthcare problems. However, I don’t think the current limited use of RL is a permanent situation just that the most exciting uses of RL are extremely difficult problems that involve long-time horizons and planning. For example, RL could be used to automatically prove mathematical theorems which would be amazing. But it’s a really hard problem for various reasons. Still a lot of progress to be made.

jmeister 6y ago

Thanks, looks very useful. Since you seem to be industry practitioners: I moved away from RL 10 yrs back disillusioned with lack of real-world applicability. Has that changed significantly? The only major name I’ve heard of is Vowpal Wabbit. Maybe there are more applications being done in stealth. Any insight? Thanks

johnmoberg 6y ago
You might be interested in the recently-launched Covariant (https://covariant.ai/ https://covariant.ai/), they apparently actually have systems in production. Pieter Abbeel is one of the founders and they have some pretty "heavy" investors, like Jeff Dean, Geoffrey Hinton, and Yann LeCun.
- jmeister 6y ago
  Thanks! OpenAI has made some progress on this problem too: https://news.ycombinator.com/item?id=21259765 https://news.ycombinator.com/item?id=21259765 Looks like these two places are on the cusp of a major breakthrough in RL/robotics!
outlace 6y ago
Honestly, not much has changed. The primary use cases continue to be things like robotics, playing games, finance etc. I’m interested in RL academically from a computational neuroscience standpoint (using RL to model cognition) but also as applied toward healthcare problems. However, I don’t think the current limited use of RL is a permanent situation just that the most exciting uses of RL are extremely difficult problems that involve long-time horizons and planning. For example, RL could be used to automatically prove mathematical theorems which would be amazing. But it’s a really hard problem for various reasons. Still a lot of progress to be made.