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#!/bin/bash
# Script to reproduce results
envs=(Hopper-v3 Walker2d-v3 Ant-v3 HalfCheetah-v3 Humanoid-v3)
steps=(1000000 1000000 3000000 3000000 10000000)
cnt=0
i=3
n_timesteps=100
for ((j=0;j<5;j+=1))
do
nohup python -u main.py \
--env_name ${envs[i]} \
--num_steps 1000000 \
--policy_type 'MLP' \
--beta_schedule 'cosine' \
--n_timesteps ${n_timesteps}\
--ratio 0.08 \
--ac_grad_norm 2 \
--action_gradient_steps 40 \
--update_actor_target_every 2 \
--seed $j \
--cuda "cuda:${cnt}" \
> "log/MLP-a_steps=40-%2-${envs[i]}-seed=${j}.log" 2>&1 &
done
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