multirotor
HighwayEnv
| multirotor | HighwayEnv | |
|---|---|---|
| 2 | 3 | |
| 12 | 2,365 | |
| - | 2.0% | |
| 7.5 | 7.5 | |
| 6 months ago | 5 days ago | |
| Python | Python | |
| - | MIT License |
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multirotor
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Show HN: I wrote a multicopter simulation library in Python
* Documentation: https://multirotor.readthedocs.io/en/latest/
* Source code: https://github.com/hazrmard/multirotor
* Demo/Quickstart: https://multirotor.readthedocs.io/en/latest/Quickstart.html
HighwayEnv
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Looking for a a tutorial/blog post/ codebase/ anything that deals with highway-env possibly the racetrack variant) with a DQN
More or less what the title says. I have already tried this https://github.com/Farama-Foundation/HighwayEnv/blob/master/scripts/sb3_racetracks_ppo.py, using a dqn from sb3 instead of the ppo but the results weren't good, i'm open to any suggestion.
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RecurrentPPO (SB3-contrib) learning for autonomous driving
Hi everyone! I'm a complete newbie to DRL, so please forgive my lack of understanding of some things on here. I'm training a recPPO from SB3-contrib on E.Leurent's Highway env [https://github.com/eleurent/highway-env] (I customized the action to be more high-level). During training I get the desired behavioural outcome from the agent but I noticed that some training metrics of the model seem quite off respect to the trend found online (especially the explained variance). I just wanted an opinion from some more navigated fellas in here! Can I somehow fix this trend by hyperparameter tuning or do I have e.g. to modify the reward function somehow? How can I improve the training? For any details I'm always available. I share the tensorboard plots obtained for RecPPO.
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Low Graphics Consuming Simulators for Self-Driving Cars
This is an excellent one https://github.com/eleurent/highway-env
What are some alternatives?
deepdrive - Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
gym-pybullet-drones - PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
deepdrive-zero - Top down 2D self-driving car simulator built for running experiments in minutes, not weeks
maze - Maze Applied Reinforcement Learning Framework
MuJoCo_RL_UR5 - A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.
simglucose - A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose
gym-md - MiniDungeons for OpenAI Gym
loopquest - A Production Tool for Embodied AI
rocket-league-gym - A Gym-like environment for Reinforcement Learning in Rocket League
PythonRobotics - Python sample codes for robotics algorithms.