Reinforced-lib

New functionalities:
- Add the normal-gamma Thompson sampling agent.
- Add the log-normal Thompson sampling agent.

Fix:
- Make it easier to import the BasicMab extension.

Important changes:
- Move to `pyproject.toml` configuration file.
- Add basic extension for MABs.
- Update dependencies.
- Fix bug modifying user values passed to library functions.
- Fix agents behavior with multiple optimal actions - now agents draw one of the optimal actions instead of selecting the first one.

Major API changes:
- Added a support for deep reinforcement learning agents.
- Relaxation of the requirements for the implementation of custom agents.
- Major changes in the logging module (e.g., custom logging, synchronization).
- Removed ability of the `sample` method to change state.
- Introduced an inference only mode.

New functionalities:
- Added new deep learning agents: deep Q-learning, deep expected SARSA, DQN, DDPG.
- Added the Exp3 algorithm.
- Added the Gymnasium extension.
- Added the TensorBoard logger.
- Added an easy export to TensorFlow Lite.
- Added an automatic checkpointing.

Other important changes:
- Upgraded the library to Python 3.9.
- Updated and polished the documentation.
- Added several new examples.
- Moved Wi-Fi specific classes to examples.
- Fixed known bugs.

- Add discounted UCB
- Rename Gradient bandit to Softmax
- Update IEEE 802.11ax extension
- Improve agent descriptions
- Extended getting started
- Add Gym integration docs
- Editorial updates in docs
- Fix major and minor bugs

- Fix missing file with requirements