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View Code? Open in Web Editor NEWExORL: Exploratory Data for Offline Reinforcement Learning
Home Page: https://sites.google.com/view/exorl
License: MIT License
ExORL: Exploratory Data for Offline Reinforcement Learning
Home Page: https://sites.google.com/view/exorl
License: MIT License
In https://github.com/denisyarats/exorl/blob/main/custom_dmc_tasks/point_mass_maze.py#L155, why there are the following modifications over the original dmc point_mass environment?
physics.data.qpos[0] = np.random.uniform(-0.29, -0.15)
physics.data.qpos[1] = np.random.uniform(0.15, 0.29)
physics.named.data.geom_xpos['target'][:] = self._target
Is it possible to release the code for data collection? Is each dataset collected using one seed or multiple seeds? Thanks in advance!
Hi,
I was trying to go through the code and couldn't understand one thing. When sampling a tuple from the replay buffer, why do action, reward and discount use index i
which is the same for next_observation
? Shouldn't they also be using index i-1
similar to observation
?
Lines 93 to 98 in a3fb07a
Hi, I tried to replicate the results from the paper by running from scratch using URL Benchmark to collect data and use your repo to relabel and train offline but could not replicate the results from the paper. Please release the data collection step to this repo for full replication of the papers results. Thanks
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