Machine Learning
Q-Learning Unleashed: Building Intelligent Agents
In this course, we focus on building a Q-learning agent step by step. We start with the Bellman equation and the Q-table update, then implement a basic Q-learning function. Next, we incorporate an exploration policy (ε-greedy), and finally we demonstrate how to use the learned Q-table for decision making.
Numpy
Python
3 lessons
15 practices
1 hour
Machine Learning Model Development
Course details
Q-Learning Update Function
Fix the Q-Learning Update Function
Handling Terminal States in Q-Learning
Calculating Temporal Difference Error
Simulate Q-Learning!
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