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Machine Learning

Navigating RL Challenges: Strategies and Future Directions

The final course explores advanced techniques to enhance our RL systems. We'll implement random goal positions, hazardous environments with mines, and reward shaping, concluding with an exploration of cutting-edge RL developments that point toward future applications.

Numpy

Python

See path

5 lessons

20 practices

1 hour

Coding and Data Algorithms

Course details

Implementing Random Goals in Grid World Environments

Preview

Random Goals in Grid World

Random Goal Positioning in GridWorld

Random Goal Selection in Grid World

Refine Random Goal Selection

Customizing Goal Distance in Grid World

Previous Course

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