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Introduction
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Classroom Contents
Data Augmentation for Image-Based Reinforcement Learning
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- 1 Introduction
- 2 Outline
- 3 Problem
- 4 Image Augmentation
- 5 Other Augmentation Strategies
- 6 Hyper Parameters
- 7 Models and Auxiliary Tasks
- 8 Results
- 9 Atari Benchmark
- 10 Image Augmentations
- 11 Summary
- 12 Dr Q
- 13 Dr Qv2
- 14 Dreamer
- 15 Conclusion
- 16 Reinforcement with prototypical representations
- 17 Limitations
- 18 Task Exploration
- 19 Selfsupervised Learning
- 20 ProtoRL Approach
- 21 Example
- 22 Importance of Exploration
- 23 Benchmarking
- 24 Wrapup
