Timeline for In what situation would you want to use NEAT over reinforcement learning?
Current License: CC BY-SA 4.0
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| Aug 31, 2022 at 16:01 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| May 3, 2022 at 15:11 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Apr 3, 2022 at 14:41 | answer | added | Junwei Dong | timeline score: 1 | |
| S Aug 15, 2021 at 5:19 | history | suggested | gerichhome |
Added tag neat
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| Aug 14, 2021 at 21:04 | review | Suggested edits | |||
| S Aug 15, 2021 at 5:19 | |||||
| Aug 13, 2021 at 21:31 | comment | added | Dylan Kerler | Yes, I'm very familiar with the de-facto RL like using PPO, Q-Learning etc. NEAT can be used to find a policy through "evolution" of both the neural net architecture and the weights in the neural net. I'm wondering in what situation would NEAT be better than policy gradient RL. | |
| Aug 13, 2021 at 20:16 | comment | added | nbro | I was just making sure that you know what RL is used for, and if you know how NEAT could be applied to RL problems. Maybe you can briefly state in your post what NEAT can be used for. To find a policy? To evolve neural networks that represent the policy that you want to find in RL? | |
| Aug 13, 2021 at 17:10 | comment | added | Dylan Kerler | Sure, in the NEAT python repo they have examples of applying NEAT to OpenAI lunar-lander and cartpole problems. Are you asking a rhetorical question (actually just asking so i dont sound dumb lol)? | |
| Aug 13, 2021 at 14:31 | comment | added | nbro | It seems that you know what NEAT can be used for. Do you know what RL is used for? If yes, can you give an example of when you think you could use NEAT rather than RL (which doesn't mean it is necessarily a better approach than RL)? | |
| Aug 12, 2021 at 11:44 | history | asked | Dylan Kerler | CC BY-SA 4.0 |