计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
simulation-environments【效率与协作】Operate built-in HighwayEnv Gymnasium environments, registration, reset-step loops, rendering, vectorization, finite-MDP helpers, and multi-agent wrappers.
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Use this sub-skill when you need to instantiate and operate built-in HighwayEnv Gymnasium environments safely. It covers environment ID selection, registration, gym.make, reset/step/render lifecycles, bounded random rollouts, vectorized environments, RecordVideo, finite-MDP helper methods, and multi-agent wrapper semantics.
terminated and truncated correctly.gym.make(..., config=...), env.unwrapped.config, or reset(options={"config": ...}).rgb_array frames, recording short videos, or avoiding display windows.env.unwrapped.to_finite_mdp(), simplify(), change_vehicles(), set_preferred_lane(), and set_route_at_intersection().intersection-multi-agent-* environments and MultiAgentWrapper return semantics.info["rewards"] details: read ../observations-actions-rewards/SKILL.md.../road-vehicle-dynamics/SKILL.md.../training-and-evaluation/SKILL.md.info, and safe episode loops.gym.make cannot find an env, rendering fails or returns None, vector/multiprocessing fails, helper methods raise optional-dependency errors, or episodes run unexpectedly long.rgb_array, and summarized as JSON.import gymnasium as gym
import highway_env
gym.register_envs(highway_env) # harmless when already registered
env = gym.make("highway-v0", config={"duration": 5, "vehicles_count": 10})
try:
obs, info = env.reset(seed=0)
terminated = truncated = False
while not (terminated or truncated):
action = env.action_space.sample()
obs, reward, terminated, truncated, info = env.step(action)
finally:
env.close()
Prefer explicit step caps for smoke checks and automation. Some scenarios can run for many decision steps, and lane-keeping-v0 relies on Gymnasium's registration time limit rather than an internal duration termination.