docs/PHASE3_IMPLEMENTATION.md

# Phase 3 Implementation Notes

Phase 3 goal: Recurrent PPO (LSTM policy) to capture temporal dependencies such as SLA trend and escalation history.

Implemented Components

• rl/train_recurrent.py
  • RecurrentPPO training with MlpLstmPolicy
  • LSTM hidden size configurable (default 128)
  • curriculum sampling retained (easy -> medium -> hard)
  • optional transfer of compatible policy tensors from best Phase 2 checkpoint
• rl/configs/recurrent.yaml
  • declarative recurrent training and curriculum settings
• rl/evaluate.py
  • model loading modes: auto, maskable, recurrent
  • recurrent inference path with LSTM state handling + action-mask sanitization
  • helper compare_recurrent_vs_flat(...)
• rl/callbacks.py
  • RecurrentEvalCallback for periodic grader-based checkpointing in Phase 3
  • recurrent best checkpoints saved as best_grader_recurrent_<task>.zip (no collision with Phase 2 files)
• rl/gym_wrapper.py
  • optional hard_action_mask mode (default off) for safe action execution
• tests/test_rl_evaluate.py
  • recurrent hidden-state persistence
  • LSTM reset behavior on episode boundary
  • recurrent >= flat comparison utility check

Commands (using existing .venv313)

• Train Phase 3:
  • .\\.venv313\\Scripts\\python.exe -m rl.train_recurrent --timesteps 600000 --n-envs 4 --seed 42 --config rl/configs/recurrent.yaml
• Train Phase 3-v2 (recommended tuning run):
  • .\\.venv313\\Scripts\\python.exe -m rl.train_recurrent --timesteps 700000 --n-envs 4 --seed 42 --config rl/configs/recurrent_v2.yaml
• Evaluate Phase 3 model:
  • .\\.venv313\\Scripts\\python.exe -m rl.evaluate --model results/best_model/phase3_final.zip --episodes 3 --model-type recurrent
• Evaluate best recurrent checkpoint (saved during Phase 3 eval):
  • .\\.venv313\\Scripts\\python.exe -m rl.evaluate --model results/best_model/best_grader_recurrent_mixed_urgency_medium.zip --episodes 3 --model-type recurrent
• Compare recurrent vs flat on medium task:
  • .\\.venv313\\Scripts\\python.exe -c "from rl.evaluate import compare_recurrent_vs_flat; print(compare_recurrent_vs_flat('results/best_model/phase2_final.zip','results/best_model/phase3_final.zip'))"