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Meta-World was designed to be both a Meta-RL and a Multi-Task RL benchmark.
One of the awkward consequences of that is that the way goal conditioning is handled is very complicated in Meta-World.
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# To Do (Urgent)
- [x] 3 types of State functions - Code Template
- [x] 3 types of Action functions - Code Template
- [x] 3 types of Reward functions - Code Template
- [x] Finish code template f…
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How would you implement a minimax q-learner with coax?
Hi there! I love the package and how accessible it is to relative newbies. The tutorials are pretty great and the accompanying videos are very…
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Hi!
Let's bring the reinforcement learning course to all the Russian-speaking community 🌏
Would you want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/tran…
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https://www.csie.ntu.edu.tw/~htlin/paper/doc/aaai15albl.pdf
Pool-based active learning is an important technique that helps reduce labeling efforts within a pool of unlabeled instances. Currently, …
leo-p updated
7 years ago
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## Weekly Notebook Entry — Week [01]
### Overview
- **Week Span:** `[9/9]` to `[9/15]`
### Tasks for This Week
List your specific objectives for this week, including learning targets and pro…
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Dear Hongzi,
I was trying to figure out the matching between the RL agent's state s(t) in the code and the input info in the paper.
**Input:** After the download of each chunk t, Pensieve’s lea…
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Dear author:
First of all, thank you for your project which has brought me a lot of inspiration. At the same time, in the part of reward function, I have a problem.
I tried to print the energy, ener…
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