Hindsight Experience Replay - Bit flipping experiment and Chase experiment in Tensorflow.
Bit Flipping implementation includes:
- Double DQN with 1 hidden layer of size 256.
- Hindsight experience replay memory with "K-future" strategy.
- A very simple bit-flipping evironment as mentioned in the original paper.
Chase Experiment includes:
- DDPG Actor-Critic implementation.
- Hindsight experience replay memory with "K-future" strategy.
- A very simple reacher environment with continuous actions.
To run this code, adjust the hyperparameters from HER.py and type
$ python dqn_her.py -h
Read about the arguments provided in the code to experiment with different options.
For bit flipping experiment
- Evaluate baseline and her for 15 bits env.
- Evaluate performance of baseline for different sizes (5-25).
- Evaluate performance of her for different sizes (5-25).
- Modify K-future strategy to final, K-episode, K-random strategies.
- Evaluate performance for different strategies.
For chase experiment
- Understand implementation of DDPG
- Check similarities and dissimilarities with DQN
- Evaluate performance for different parameter values.
- DQN+HER: Mostly based on implementation by minsangkim142.
- DDPG+HER: Mostly based on implementation by kwea123.