Building on the foundational knowledge from Part 1, this session delves deeper into advanced Reinforcement Learning algorithms and techniques. Participants will explore policy-based methods, value-based methods, and model-based approaches. Through
hands-on projects, attendees will implement and experiment with these advanced algorithms in various scenarios.
Date & Time
Wednesday September 18th, 2024 9:45am EDT
End Date & Time
Wednesday September 18th, 2024 10:45am EDT
Venue
Calusa F
Speakers
Ajay Gomez
Session Format
Standard 60 Minute Session
Learning Objectives
1. Explore advanced Reinforcement Learning algorithms, including policy gradients and Q-learning.
2. Understand the differences and applications of policy-based, value-based, and model-based RL methods.
3. Implement advanced RL algorithms in code and apply them to more complex problems.
2. Understand the differences and applications of policy-based, value-based, and model-based RL methods.
3. Implement advanced RL algorithms in code and apply them to more complex problems.
Session Level
Beginner
Conference
NAViGATE Florida
Session Comments