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A Neurally Plausible Model Learns Successor Representations in Partially Observable Environments

A Neurally Plausible Model Learns Successor Representations in Partially Observable Environments

Yannic Kilcher via YouTube Direct link

Introduction

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Introduction

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Classroom Contents

A Neurally Plausible Model Learns Successor Representations in Partially Observable Environments

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  1. 1 Introduction
  2. 2 Reinforcement learning
  3. 3 successor representations
  4. 4 value functions
  5. 5 continuous space
  6. 6 distributional coding
  7. 7 wake and sleep
  8. 8 mu

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