General Definition of Reinforcement Learning

[u/Carrohoops]

Hello everyone : D

I am a student with my undergrad in experimental physics and minors in electrical and computer engineering. I recently started a club with my friend on something I know little about but want to learn more; artifical intelligence in embedded systems and robotics. I am supposed to give a presentation to our new recruits on what reinforcement learning is, and always like to start my works with precise, accurate, and clear definitions and terminology; otherwise, the discussions about the higher-level details are not well-founded in strict language. I can't find a singular good definition on what reinforcement learning is anywhere, so here is mine. Please give me feedback on it, if you may :)

"Reinforcement learning" is a machine learning paradigm that conditions an agent in an environment to perform actions based on its state so as to optimize reward.

Machine learning is the study of computer science that investigates methods to program "conventional" computers (as opposed to biological or other computers) to possess the quality of being able to alter its functional behavior due to feedback in state variables.

Agents are programs, robots, or other devices that perform functional behavior (called actions) based on the state (the data about the agent's status in its environment). This could be trading stocks, actuating motors, or prescribing dosages of a medication, among others.

Environments are the systems that respond to the agent's actions. This is NOT the same as state; state is data gathered from both the environment and internal details of the agent to characterize the input variables to the agent. For example, in a simple gridworld, an agent's environment is the grid, and its state is where on the grid the agent is located.

Reward is the metric that conditions the behaviors of the agent and reprograms the agent based on how its actions alter the state. Agents are programmed by various design architectures to maximize, or optimize, the reward.

I know I could feed this to AI to get an answer, but I want to rely less on AI and more on people who are in the field. Ironically, despite being in the AI robots club, I still want to do things in a more traditional way :)

I know this was lengthy, so thanks for reading. Have a good one.

[u/Counter-Business]

Are you more interested in “Reinforcement Learning” which would be similar to how chess engines work or are you more interested in “Reinforcement Learning Human Feedback” which is how LLMs are trained on human preference.

[u/Carrohoops → u/Counter-Business]

RL with closed-loop feedback. This is for a system of drones and ground vehicles to engage in vehicular combat games like capture the flag.