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Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

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Using k=5, n=100, MAML fails to learn: average training and validation returns consistently hover around 50 throughout all 500 outer loop steps. Any possible discrepancies between this repo's code/config and...

**I run:** python train.py --config configs/maml/bandit/bandit-k5-n10.yaml --output-folder bandit/bandit-k5-n10/ --seed 1 --num-workers 8 **but fail:** Process SamplerWorker-1: Process SamplerWorker-2: Process SamplerWorker-3: Traceback (most recent call last): Traceback (most recent call last):...

I write a new environment (navigation on deterministic map): (1) I run " python train.py --config xxxx", and get config.json, policy.th. (2) I run "python test.py -config xxxx", and get...

Thanks for this great work! I'd like to konw if iwant employe the meta-rl on the new env (such as carla), what should i do

Hi, Thank you so much for the codes. I see that cuda may not be supported in many cases. I'm guessing this is due to multiprocessing, which I am not...

I find you have update your code recently. Your work is very amazing to me, I really thank you very much. But I also find that your code can't run...

I couldn't find a pre-trained policy hosted here, so I trained my own using the suggested command in the readme (saving each iteration). You can find a zip with all...

Hi, thanks for your code which gives me a lot of help. But I have a question about the AntVel env, when I tried to train MAML in this environment,...

- Adapt `AntEnv` and `HalfCheetahEnv` from [rllab](https://github.com/rll/rllab) to work as a Gym environment, and use them for the continuous control experiments - The [original code](https://github.com/cbfinn/maml_rl/) uses variants of the RLlab's...

Hi, this is fantastic resource, Thanks for sharing this! BTW, I ran AntDir-v1, and AntVel-v1, I ran 2~3 times, but it doesn't seem to learn at all. I could successfully...