executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
on-policy-actor-criticRouter for REINFORCE, baseline, actor-critic, A2C, and PPO workflows.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill for the repo's on-policy classic-control workflows in Char02, Char03, Char04, and Char07.
SubprocVecEnv in Char04.references/workflows.md for the algorithm comparison, checkpoint map, and the exact source-script roles.references/troubleshooting.md for env.seed, old Gym step signatures, multiprocessing, checkpoint loading, TensorBoard paths, and headless plotting failures.scripts/multiprocessing_env.py for the reusable subprocess vector-env helper used by A2C.scripts/playback_saved_policy.py for bounded playback of saved policy pickles from the REINFORCE / actor-critic family.saved_log_probs: REINFORCE.G - V: actor-critic or baseline.clip_param, ratio clipping, minibatches, repeated epochs: PPO..pkl policy object that should be evaluated rather than trained: playback helper.step(...) tuples.env.seed(...) and legacy env IDs such as CartPole-v0, MountainCar-v0, and Pendulum-v0.Pendulum-v0 as a compatibility note; use Pendulum-v1 in the inspected environment when you need a modern substitute.