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hindsight_experience_replay

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A tensorflow implementation of hindsight experience replay

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# Hindsight Experience Replay (HER)

This repository contains a tensorflow HER implementation and a bit flipping environment as described in [OpenAI's paper](https://arxiv.org/pdf/1707.01495.pdf)

The implementation includes :

1. In `Hindsight Experience Replay.ipynb` :
    1.  A DQN and a DDQN agent (which also work on other traditional [gym](https://gym.openai.com/) environments)
    2.  A bit flipping environment
    3.  Pre-trained models for 30-bits, 40-bits and 50-bits flipping environments
2. In `ChaseEnv_DDPG.ipynb` :
    1. A DDPG agent
    2. A `ChaseEnv` environment, where a chaser is initialized at a random position in
       a 2d plane and has to reach a goal in another random position within a certain threshold.

## Benchmarks

*  100% success rate for 30 and 40-bits environments
*  95% success rate for 50-bits environment (average on 100 tests)
*  90% success rate for size=5 ChaseEnv (average on 100 tests)

## Customize
Check the "Training" cell to adjust training parameters and enable/disable HER.

## TODO
- [x] Optimize the way to concatenate transitions
- [ ] Parallelize training
- [x] Train on bit length > 30
- [x] Implement DDPG

## Extra
[Here](https://github.com/kwea123/RL/blob/master/ai/unity_test/robot_arm/robot_arm_3d_ddpg_her_sparse.ipynb) is a link to a robot arm reach environment created in Unity, trained with [ML-Agents](https://github.com/Unity-Technologies/ml-agents).

This environment is trained using DDPG with and without HER, and the comparison is plotted. DDPG+HER performs better.

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