Important Notice: All event details including program and schedule are tentative and subject to change. Speakers are confirmed.

Program Schedule

Detailed agenda for the 2nd Reinforcement Learning Bootcamp

View Schedule Meet the Speakers
RL Bootcamp Program

Program Overview

A comprehensive look at our three-day event

Note: This program is tentative and subject to change as we finalize details.

Our program is designed to provide a comprehensive introduction to reinforcement learning, from basic concepts to advanced applications. The bootcamp spans three full days, with a mix of theoretical lectures, hands-on workshops, and networking opportunities.

Schedule

Detailed agenda for September 17-19, 2025

Tentative Schedule: The following schedule is tentative and may be adjusted as we finalize workshop details.

Day 1: Wednesday, September 17

11:00 - 13:00 Arrival
13:00 - 14:00 Lunch Break at ARGE beisl:Ulrike-Gschwandtner-Strasse 5
14:00 - 14:30 Opening and Introduction
14:30 - 15:30 Lecture 0 I - Introduction to Reinforcement Learning
15:30 - 16:00 Coffee Break
16:00 - 17:00 Lecture 0 II - RL Fundamentals
17:00 - 18:00 Networking Break
18:00 - 19:00 Keynote (Online): Prof. Sergey Levine (UC Berkeley) - "Recent Advances in Deep Reinforcement Learning"
19:30 - 21:00 Dinner at ARGE beisl:Ulrike-Gschwandtner-Strasse 5

Day 2: Thursday, September 18

9:30 - 10:15 Keynote: Prof. Peter Auer (University of Leoben) - "Multi-Armed Bandits and Exploration Strategies"
10:15 - 11:00 Keynote: Dr. Samuele Tosatto (University of Innsbruck) - "Where are all the intelligent robots? A quest for efficiency in reinforcement learning"
11:00 - 11:30 Coffee Break
11:30 - 12:30 Policy Gradients and Actor Critics I
12:30 - 13:30 Lunch at ARGE beisl:Ulrike-Gschwandtner-Strasse 5
13:30 - 14:30 Policy Gradients and Actor Critics II
14:30 - 15:30 Hands-On Workshop "Implementing PPO from Scratch" (setup and intro)
15:30 - 16:00 Coffee Break
16:00 - 18:00 Hands-on Workshop: "Implementing PPO from Scratch"
19:00 - 21:00 Dinner at Die Weisse:Rupertgasse 10

Day 3: Friday, September 19

9:30 - 11:00 Hands-on Workshop
11:00 - 11:30 Coffee Break
11:30 - 12:30 State of the art in deep reinforcement learning
12:30 - 13:00 Final Round and Closing Remarks
13:00 - 14:00 Lunch at ARGE beisl:Ulrike-Gschwandtner-Strasse 5
15:00 - 17:00 Salzburg Visit

Speakers

Meet our expert speakers and instructors

Sergey Levine

Prof. Sergey Levine

UC Berkeley

Pioneering researcher in deep reinforcement learning and robotic control

Peter Auer

Prof. Peter Auer

University of Leoben

Leading expert in multi-armed bandits and exploration strategies

Samuele Tosatto

Dr. Samuele Tosatto

University of Innsbruck

Specialist in policy optimization for reinforcement learning

Workshops & Deep Lectures

Intensive learning experiences combining theory and practice

Setting Up Your RL Environment

Configure Python environments with PyTorch, TensorFlow, and Gymnasium for state-of-the-art RL experimentation.

Implementing PPO from Scratch

Build a Proximal Policy Optimization algorithm implementation step-by-step, with detailed code walkthroughs.

Building World Models for RL

Learn to create and train neural network models of environments to improve sample efficiency in RL training.

Multi-Agent Systems Implementation

Design and implement collaborative and competitive multi-agent reinforcement learning systems.

Advanced Policy Gradient Methods

In-depth exploration of state-of-the-art policy optimization techniques including PPO, TRPO, and SAC.

Model-Based Reinforcement Learning

Comprehensive review of model-based RL approaches, from Dyna-Q to modern deep learning architectures.

Multi-Agent Reinforcement Learning

Theoretical foundations and practical implementations of MARL algorithms, coordination mechanisms, and emergent behaviors.