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RL-Sim-Framework/configs/training/ppo_real.yaml
2026-03-11 22:52:01 +01:00

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# PPO tuned for single-env real-time training on real hardware.
# Inherits defaults + HPO ranges from ppo.yaml.
# ~50 Hz control × 1 env = ~50 timesteps/s.
# 100k timesteps ≈ 33 minutes of wall-clock training.
defaults:
- ppo
- _self_
hidden_sizes: [256, 256]
total_timesteps: 100000
learning_epochs: 5
learning_rate: 0.001 # conservative — can't undo real-world damage
entropy_loss_scale: 0.0001
log_interval: 1024
checkpoint_interval: 5000 # frequent saves — can't rewind real hardware
initial_log_std: -0.5 # moderate initial exploration
min_log_std: -4.0
max_log_std: 0.0 # cap σ at 1.0
# Never run real-hardware training remotely
remote: false
# Tighter HPO ranges for real hardware (override base ppo.yaml ranges)
hpo:
entropy_loss_scale: {min: 0.00005, max: 0.001}
learning_rate: {min: 0.0003, max: 0.003}