Reinforcement_Learning_in_Python
Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa
Navigate a mobile robot through unknown environments using Q-learning and Sarsa algorithms for path planning.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeImplementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa
Reinforcement_Learning_in_Python has 511 stars on GitHub. It has been forked 117 times. Reinforcement_Learning_in_Python is written mainly in Python. It has been in active development since 2018. Reinforcement_Learning_in_Python is available under the MIT license. Its main topics are maze-algorithms, maze-solver, obstacle-avoidance, path-planning.
What is Reinforcement_Learning_in_Python?
Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa
Is Reinforcement_Learning_in_Python open source?
Reinforcement_Learning_in_Python is an open-source project. It is released under the MIT license.
Is Reinforcement_Learning_in_Python free?
Yes. Reinforcement_Learning_in_Python is free and open source — you can use, modify and self-host it.
What license does Reinforcement_Learning_in_Python use?
Reinforcement_Learning_in_Python is available under the MIT license.
What language is Reinforcement_Learning_in_Python written in?
Reinforcement_Learning_in_Python is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/sichkar-valentyn-reinforcement-learning-in-python.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.