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run.sh
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run.sh
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python training_baseline_policy.py --env_id "CheeseMaze-v0" --k 1 --training_episodes 5000 --decaying_rate_qlearning 0.002 --beta 15
python training_baseline_policy.py --env_id "Tiger-v0" --k 1 --training_episodes 5000 --decaying_rate_qlearning 0.002 --beta 0.05
python training_baseline_policy.py --env_id "Voicemail-v0" --k 1 --training_episodes 5000 --decaying_rate_qlearning 0.002 --beta 0.3
python training_baseline_policy.py --env_id "Tiger-v0" --k 0 --training_episodes 5000 --decaying_rate_qlearning 0.002 --beta 0.05
python training_baseline_policy.py --env_id "Voicemail-v0" --k 0 --training_episodes 5000 --decaying_rate_qlearning 0.002 --beta 0.3
python main.py -c 8 -s $(seq -s \ 1 500) -p data/CheeseMaze-v0_k-1.pkl
python main.py -c 8 -s $(seq -s \ 1 500) -p data/Tiger-v0_k-1.pkl
python main.py -c 8 -s $(seq -s \ 1 500) -p data/Voicemail-v0_k-1.pkl
python main.py -c 8 -s $(seq -s \ 1 500) -p data/Tiger-v0_k-0.pkl --target_ks 0 1
python main.py -c 8 -s $(seq -s \ 1 500) -p data/Voicemail-v0_k-0.pkl --target_ks 0 1