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Measure sample efficiency and generalization in reinforcement learning using procedurally generated environments
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graded | 77348 | ||
failed | 77203 |
Sample-efficient reinforcement learning in Minecraft
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5 Problems 15 Days. Can you solve it all?
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See Allgraded | 72729 | ||
graded | 72725 | ||
graded | 72719 |
5 PROBLEMS 3 WEEKS. CAN YOU SOLVE THEM ALL?
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Latest submissions
See Allgraded | 72729 | ||
graded | 72725 | ||
graded | 72719 |
Multi-Agent Reinforcement Learning on Trains
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NeurIPS 2020: Procgen Competition
Ray Error with TF and CUDA
Over 4 years ago(topic withdrawn by author, will be automatically deleted in 24 hours unless flagged)
Insufficient cluster resources to launch trial
Over 4 years ago(post withdrawn by author, will be automatically deleted in 24 hours unless flagged)
Strategy to achieve objective
Over 4 years agoI am still un certain of the direction of reaching the objective. do we tweak the hyperparams of the algorithms available and tweak model or are we meant to create brand new algorithms for RL. Or do we just create custom models. I will love to try latest CV models as well. but i donβt know if i am allowed to use PyTorch models created from scratch and using custom algorithms.
Insufficient cluster resources to launch trial
Over 4 years agoray.tune.error.TuneError: Insufficient cluster resources to launch trial: trial requested 7 CPUs, 0.8999999999999999 GPUs but the cluster has only 2 CPUs, 1 GPUs, 1.37 GiB heap, 0.63 GiB objects (1.0 node:192.168.1.242). Pass queue_trials=True
in ray.tune.run() or on the command line to queue trials until the cluster scales up or resources become available.
SO I understand what this error means but i donβt know if i need to repair it before i begin working on the project. I also need some advice on how to fix it.
Error running code
Over 4 years agoi keep getting this error, even though i have downgraded to torch 1.3.1
File β/home/dewe/anaconda3/envs/procgen/lib/python3.7/site-packages/ray/rllib/models/model.pyβ, line 198, in flatten
return torch.flatten(obs, start_dim=1)
TypeError: flatten(): argument βinputβ (position 1) must be Tensor, not Tensor