PPO CartPole View

This file visualizes the training curve produced by NN/Examples/Models/RL/PPOCartPole.lean (lake -R -K cuda=true exe torchlean ppo_cartpole --device cuda ...).

The executable trainer and this editor-side view live together under Examples/Models/RL.

Workflow:

1. Run:

python3 -m pip install --user 'gymnasium>=1.0'
lake -R -K cuda=true exe torchlean ppo_cartpole --device cuda --updates 1 --eval-every 1 \
  --eval-episodes 1 --eval-max-steps 8

2. Put the cursor on the command below in an editor. The infoview will render the saved log.

Notes:

• The executable writes data/rl/ppo_cartpole_trainlog.json by default (override with --log).
• This viewer is pure: if the file is missing, it shows an error panel instead of failing to build.

References:

• Schulman et al., "Proximal Policy Optimization Algorithms" (2017): https://arxiv.org/abs/1707.06347
• Schulman et al., "High-Dimensional Continuous Control Using Generalized Advantage Estimation" (2015): https://arxiv.org/abs/1506.02438