* add torch coma

* add Apache License comment

* update readme

* update readme for installing sc2 on windows

* update readme

* add new line at the end of shell file

* update readme

* update readme of coma

* fix model_path

* self.algorithm to self.alg
Co-authored-by: NBo Zhou <2466956298@qq.com>

- add prioritized dqn
- fix#239

* fix self.alg

* torch agent initialization

* remove definition of self.alg in PPO

* replace self.algorithm with self.alg

* remove unnecessary definition of self.alg

* fix cn readme

* unittest

* yapf

* add ppo

* fix bugs

* yapf

* upgrade DQN's lr interface compatibility

* yapf

* update example DQN

* ping the master before connection

* yapf

* fix comments

* remove the useless library

* install ping for the docker environment

* remove protobuf intallation

* remove evokit test

* replace tensorboard with summary to support VDL in the future

* unittest

* rename keys for record

* yapf

* state to obs

* yapf & update softlink in offline-q-learning

* remove version 1.3 warnings

* update

* yapf

* add algorithms test

* Update algs_test.py

* Update algs_test.py

add SAC DDPG TD3 tests

* yapf

* fix a2c cannot run in paddle 1.6.0

* fix impala compatibility

* yapf

* fix compatibility issue with the newest paddle

* remove logging lines

* resolve the compatibility issue with the newest paddle

* yapf
Co-authored-by: Nrobot <zenghongsheng@baidu.com>

* fix compatibility issue with the newest paddle

* remove logging lines
Co-authored-by: Nrobot <zenghongsheng@baidu.com>

* update comments for ES

* check dependence on paddle or torch

* update readme

* update readme#2

* users can still use parl.remote when no DL framework was found

* yapf

* add maddpg example

* format with yapf

* fix coding style

* fix coding style

* unittest without import multiagent env

* update maddpg code

* update maddpg readme

* add copyright comments

* update parl.maddpg without import gym

* update NeurlIPS2018.gif to NeurlIPS2019.gif

* update readme and comments

* torch benchmark policy gradient

* refine comments and use native api

* add maddpg example

* format with yapf

* fix coding style

* fix coding style

* unittest without import multiagent env

* update maddpg code

* update maddpg readme

* add copyright comments

* add sac

* Training pipeline of NeurIPS2019-Learn-to-Move-Challenge

* fix grammar mistakes

* release 1.2.1

* copyright

* fix bug

* refine README

* refine README

* fix typo

* Update README.md

* Update README.md

* add TD3

* update

* yapf.....

* Update train.py

* add pytorch a2c

* add set/get_weights test & copyright

* yapf....

* Update model_base_test_torch.py

* update

* Delete banma.py

* Update model_base_test_torch.py

* update

* Update model.py

* update torch tests

* Update model_base_test_torch.py

* add Double & Dueling DQN

* yapf......................

* update

* Update train.py

* git commit -m torchdqn

* yapf

* fix bugs

* fix bugs

* fix bugs

* yapf

* remove fstring format

* torch_test yapf

* yapf

* Add torch in unittest.requirements

* update torch_unittest

* Torch and FLUID conflict problem in __init__.py

* Unittest fail for torch when both torch and fluid exists.

* cluster_test fail in the unittest, add timeout seconds.

* Torch backend for PARL

* add sleep time for unit test send_job_test.py

* Unit test for send_job_test.py

* use multiple try for unit test

* Fix compatibility for python2.7.

* fix send_job_test.py bugs

* check file exist before send_job_test.py

* Modify send_job_test.py

* fix bug of ParamAttr

* refine imports of unittest

* remove previous algorithms; use the forward function in parl.Model

* remove abundant lines

* yapf

* intra-version: move parl.framework into parl.core.fluid

* add folder: parl.core

* remove former test folders

* yapf

* yapf0.24

* add IMPALA algorithm and some common utils

* update README.md

* refactor files structure of impala algorithm; seperate numpy utils from utils

* add hyper parameter scheduler module; add entropy and lr scheduler in impala

* clip reward in atari wrapper instead of learner side; fix codestyle

* add benchmark result of impala; refine code of impala example; add obs_format in atari_wrappers

* Update README.md

* add a3c algorithm, A2C example and rl_utils

* require training in single gpu/cpu

* only check cpu/gpu num in learner

* refine Readme

* update impala benchmark picture; update Readme

* add benchmark result of A2C

* move get_params/set_params in agent_base

* fix shell script cannot run in ubuntu

* refine comment and document

* Update README.md

* Update README.md

* add IMPALA algorithm and some common utils

* update README.md

* refactor files structure of impala algorithm; seperate numpy utils from utils

* add hyper parameter scheduler module; add entropy and lr scheduler in impala

* clip reward in atari wrapper instead of learner side; fix codestyle

* add benchmark result of impala; refine code of impala example; add obs_format in atari_wrappers

* Update README.md

* add PPO example

* Update Readme

* Update Readme

* fix codestyle

* Update Readme

* refine action mapping

* add more unitest case

* remove unnecessary params initialize, add more comments, add benchmark result

* rename

* remove PARL dependence in readme of examples

* add DDPG example, fix some tiny bug

* add license

* unify code structure

* unify code structure

* refine gputils, fix seed in QuickStart

* use white noise in DDPG

* fix codestyle

* add QuickStart example, refine DQN example

* add examples link

* refine the naming, and add quick start training result

* add DQN example, add Agent unittest

* refine readme

* refine  code

* simplify code