# soft-Q-learning

**Repository Path**: ChenGouXiang/soft-Q-learning

## Basic Information

- **Project Name**: soft-Q-learning
- **Description**: discrete soft Q learning(SQL) and soft Q imitation learning(SQIL) implementation in pytorch, simple!
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 1
- **Created**: 2020-04-22
- **Last Updated**: 2023-05-25

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# SQL & SQIL

the implement of soft Q learning algorithm in pytorch

**note that this is for discrete action space**

**update SQIL: soft q imitation learning**

all code is in one file and easily to follow

## requirment

- tensorboardX (for logging, you can delete the logging code if you don't need)
- pytorch (>= 1.0, 1.0.1 used in my experiment)
- gym

in Cartpole-v0

## Ref
[Reinforcement Learning with Deep Energy-Based Policies](https://arxiv.org/abs/1702.08165)

[SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards](https://arxiv.org/abs/1905.11108v3)