A tool package for Onsite
Project description
Project description
Onsite is a tool package for Onsite.
Update
-
Version 0.1.1
Bug fixing.
-
Version 0.1.0
Add feature: Automatically output test results into output dir.
Installation
To get started, you'll need to have Python 3.6+ installed. Simply install onsite using pip:
pip install onsite
And you’re good to go!
Usage
The usage of this library refered to the well-known reinforcement learning library OpenAI Gym.
A simple example:
# make env from scenario (OpenScenario XML)
env,observation = onsite.env.make(scenario,output_dir)
while True:
# planning based on observation
action = planner.act(observation)
# obtain new observations from env
observation,reward,done,info = env.step(action)
# stop simulation if done
if done:
break
This is just an implementation of the classic “agent-environment loop”. Each timestep, the agent chooses an action, and the environment returns an observation and a reward.
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