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Hi, I am new to metaworld. I find that you set a max_path_length in metaworld/envs/mujoco/mujoco_env.py. I find that you mentioned this in #39, where you said it is because Mujoco environments have a max_path_length of 150.
But I find that in other mujoco envs (like openai gym), there is no such timestep limit. So I just delete line 101 and 102 in metaworld/envs/mujoco/mujoco_env.py to unrestrict the limit. Then I just run an env from your benchmark envs for 1000 timesteps and I don't encounter any problem. So I just wonder if this timestep limit is useful.
The text was updated successfully, but these errors were encountered:
The max_path_length limit is intended to ensure that results generated with metaworld are reproducible across research papers. The performance of two algorithms can be drastically different using two different max_path_length numbers, given the same number of environment samples. This is especially true in the case of meta-learning, which typically uses trajectories during the adaptation step. It also functions to give users a reasonable idea of how long an environment takes to solve.
I'll take this issue as feedback for future revisions of the benchmark. It may be artificially-constraining to limit the max_path_length, when we can already measure the total environment steps taken during training regardless of max_path_length (and in the case of meta-RL, the total environment steps prior to adaptation).
If you plan on writing a research paper, please note: regardless of your perspective on design decisions, it's never valid to report results in a research paper as "metaworld" using a modified version of the benchmark code. If a limitation is particularly-cumbersome and you need to change it, we ask that you present the results from both the modified and unmodified version of the benchmark in all figures/tables/plots, and make clear in the main text the exact modifications you made.
Hi, I am new to metaworld. I find that you set a
max_path_length
inmetaworld/envs/mujoco/mujoco_env.py
. I find that you mentioned this in #39, where you said it is becauseMujoco environments have a max_path_length of 150
.But I find that in other mujoco envs (like openai gym), there is no such timestep limit. So I just delete line 101 and 102 in
metaworld/envs/mujoco/mujoco_env.py
to unrestrict the limit. Then I just run an env from your benchmark envs for 1000 timesteps and I don't encounter any problem. So I just wonder if this timestep limit is useful.The text was updated successfully, but these errors were encountered: