Deep Reinforcement Learning --- Value Based Methods --- Chapter 2-3 Navigation

Deep Reinforcement Learning — Value Based Methods — Chapter 2-3 Navigation

1.Unity ML-Agents

2. The Environment -Introduction

  A reward of +1 is provided for collecting a yellow banana, and a reward of -1 is provided for collecting a blue banana. Thus, the goal of your agent is to collect as many yellow bananas as possible while avoiding blue bananas.

  The state space has 37 dimensions and contains the agent’s velocity, along with ray-based perception of objects around the agent’s forward direction.

 Four discrete actions are available, corresponding to:
0 - move forward.
1 - move backward.
2 - turn left.
3 - turn right.

 The task is episodic, and in order to solve the environment, your agent must get an average score of +13 over 100 consecutive episodes.

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