I have to start writing a thesis for my master's degree. The thesis itself is about machine learning. In particular, I developed an environment that simulate a real world robotic system and applied some of the most famous reinforcement learning algorithms to it. I would like to receive some tips on how to organize it in an effective way.
Right now, my idea is to organize it in the following sections:
- Abstract - Briefly introduce the topic of the thesis explaining what will be covered next.
- State of the art - Introduction to the topic of machine learning, in particular reinforcement learning (how much in detail should I go since there is a section dedicated to the agents?)
- Tools - A list of all the tools used. Basically the simulator and some machine learning libraries.
- Simulation - Explain in details how the simulation works. That is, how the robotic system physically works.
- Environment - Explain the environment is structured. That is, how the robotic system is controlled. (should this be merged with "Simulation"?)
- Agents - Explain how the different RL algorithms work in detail.
- Results - A lot of plots and tables and some explanations regarding the results of the training of the different algorithms.
- Conclusion - What I've done, what I've not, what could be done better in the future.
This question could be opinion based but exist some common rules when writing a thesis of which I'm not fully aware. I'm more interested in the latter but of course, if you want to share your opinion it will be welcomed.
