Title: Towards effective strategies for mobile robot using Reinforcement Learning

If you want to run using keyboard keys and play it by yourself, then please use the next command:

python src/main.py

To run using random moves, please use:

python src/main.py --algorithm=Random

The project aimed to find an effective strategy for a mobile robot to collect cans using a combination of a heuristic function and a BFS algorithm. The robot's behaviour was guided by a reinforcement learning agent based on its battery charge level. The environment was modelled as a finite Markov Decision Process (MDP) with defined transition probabilities and expected rewards.

https://journals.ontu.edu.ua/index.php/atbp/article/view/2522

Shaposhnikova, S., & Omelian, D. (2023). TOWARDS EFFECTIVE STRATEGIES FOR MOBILE ROBOT USING REINFORCEMENT LEARNING AND GRAPH ALGORITHMS. Automation of Technological and Business Processes, 15(2), 24-34. https://doi.org/10.15673/atbp.v15i2.2522