Dive into the fascinating world of Reinforcement Learning (RL) — the branch of AI where agents learn by interacting with their environment to maximise rewards.
In this tutorial, we explore the intuition behind policy gradients, a key concept that powers advanced RL systems used in robotics, gaming, and autonomous control.
Timestamps:
00:00:00 – Intro
00:01:11 – Why Reinforcement Learning?
00:06:04 – Policy
00:11:45 – The Objective of RL
00:17:45 – Random Policy Search
00:28:59 – Policy Gradient
00:41:19 – Q&A
Key Takeaways:
- Understand the core idea of policy-based learning in RL.
- Learn how agents improve decisions through gradient optimisation.
- Discover the link between exploration, rewards, and performance.
- Build intuition for how machines learn strategies through experience.
#DeepLearningIndaba2025 #ReinforcementLearning #PolicyGradients #MachineLearning #AI #DeepLearning #RL #AIResearch Dive into the fascinating world of Reinforcement Learning (RL) — the branch of AI where agents learn by interacting with their environment to maximize rewards.
In this tutorial, we explore the intuition behind policy gradients, a key concept that powers advanced RL systems used in robotics, gaming, and autonomous control.
Timestamps:
00:00:00 – Intro
00:01:11 – Why Reinforcement Learning?
00:06:04 – Policy
00:11:45 – The Objective of RL
00:17:45 – Random Policy Search
00:28:59 – Policy Gradient
00:41:19 – Q&A
Key Takeaways:
-Understand the core idea of policy-based learning in RL.
Learn how agents improve decisions through gradient optimization.
Discover the link between exploration, rewards, and performance.
Build intuition for how machines learn strategies through experience.
#DeepLearningIndaba2025 #ReinforcementLearning #PolicyGradients #MachineLearning #AI #DeepLearning #RL #AIResearch