Reinforcement Learning – Introduction: How Agents Learn Through Experience
Hands-on introductory workshop exploring how AI agents learn through experience, feedback, and trial and error using reinforcement learning.
How can artificial intelligence learn when existing training data is insufficient or the best solution to a problem is not yet known? The workshop “Reinforcement Learning – Introduction: How Agents Learn Through Experience,” organized by the AI Service Center Berlin-Brandenburg at the Hasso Plattner Institute, introduces participants to a machine learning approach in which AI agents improve their behavior through interaction with their environment.
In reinforcement learning (RL), agents explore different actions and receive feedback through rewards or penalties. Over time, this feedback helps them develop strategies for achieving specific goals. Participants will learn and explore fundamental concepts, including the interaction between agents and their environments, the balance between exploration and exploitation, and the design of suitable reward signals.
The workshop provides an accessible introduction to a field with applications in robotics, logistics, control systems, gaming, and simulations. No previous reinforcement learning experience is required, although basic Python knowledge is expected.
- Date: November 24, 2026
- Time: 10:00 AM–1:00 PM
- Location: Hasso Plattner Institute, Main Building (H), Room H-2.57/58, Prof.-Dr.-Helmert-Straße 2–3, 14482 Potsdam
- Organizer: AI Service Center Berlin-Brandenburg at HPI
- Admission: Free, binding registration via Eventbrite
- Language: German
- Audience: Beginners interested in reinforcement learning with basic Python knowledge
- Focus: Reinforcement learning, AI agents, learning through experience, reward mechanisms, exploration vs. exploitation, and agent-environment interaction
- Applications: Robotics, logistics, control systems, gaming, and simulations
- Practical component: Introduction to and exploration of fundamental reinforcement learning concepts
- Prerequisites: Basic Python knowledge; no prior experience with reinforcement learning required
- What to bring: A laptop
- Note: Photo, audio, and video recordings will be made during the event