Comparing multiple RL Algorithms

Recently I tried out a very interesting PyTorch challenge: getting two robots to play tennis against each other, with agents from stock-trading.

Let’s review the agents we’re going to be using:

1. Turtle-trading agent
2. Moving-average agent
3. Signal rolling agent
4. Policy-gradient agent
5. Q-learning agent
6. Evolution-strategy agent
7. Double Q-learning agent
8. Recurrent Q-learning agent
9. Double Recurrent Q-learning agent
10. Duel Q-learning agent
11. Double Duel Q-learning agent
12. Duel Recurrent Q-learning agent
13. Double Duel Recurrent Q-learning agent
14. Actor-critic agent
15. Actor-critic Duel agent
16. Actor-critic Recurrent agent
17. Actor-critic Duel Recurrent agent
18. Curiosity Q-learning agent
19. Recurrent Curiosity Q-learning agent
20. Duel Curiosity Q-learning agent
21. Neuro-evolution agent
22. Neuro-evolution with Novelty search agent

Cited as:

@article{mcateer2018rlcomp,
  title   = "Comparing multiple RL Algorithms",
  author  = "McAteer, Matthew",
  journal = "matthewmcateer.me",
  year    = "2018",
  url     = "https://matthewmcateer.me/blog/comparing-multiple-rl-algorithms/"
}

If you notice mistakes and errors in this post, don’t hesitate to contact me at [contact at matthewmcateer dot me] and I would be very happy to correct them right away!

See you in the next post 😄