In this example we implement a simple Deep Reinforcement Learning solution for the classic CartPole problem. We implement a custom reward function and then we use three different strategies to strike a balance between exploration and exploitation and use DQN to approximate Q-values:
- Epsilon greedy exploration
- Noisy Networks
- Thompson Sampling
Tasks: Reinforcement Learning
Task Categories: Reinforcement Learning
Published: 03/29/23