Experiential learning is a process of learning through direct experience, where individuals engage in activities, reflect on their actions, and apply what they’ve learned to new situations. Rather than solely reading or listening, learners actively participate, often experimenting, making mistakes, and adapting.

"Man is a 'homo discens,' a learning being. People learn as long as they live. Life is inseparably connected with learning." Horst Siebert

Reinforcement learning (RL) is a machine learning paradigm where an agent learns to make decisions by interacting with an environment. Instead of being told what to do, the agent takes actions and receives feedback in the form of rewards or penalties. The goal is to maximize cumulative rewards over time by discovering an optimal strategy, known as a policy. RL is inspired by trial-and-error learning in humans and animals, where behavior improves through experience. It’s particularly useful for tasks with sequential decision-making, such as robotics, game playing, and autonomous systems, where actions impact not only immediate rewards but also future outcomes.

Teaching, Pedagogy, Didactics