* 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

* add GA3C example

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* refine Readme

* add benchmark

* add default safe eps in numpy logp calculation

* refine document; make unittest stable

* 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

* remove not used files, add benchmark for DQN and DDPG, add Parameters management Readme

* Update README.md

* Update README.md

* add parl dependence in examples, use np shuffle instead of sklean

* fix codestyle

* refine readme of nips example

* fix bug

* fix code style

* Update README.md

* Update README.md

* Update README.md

* refine document and remove outdated design doc

* Update README.md

* Update README.md

* refine comment

* release version 1.0

* gif of examples

* Update README.md

* update Readme

* sync paras in program, fix deepcopy bug, python3 compatibility

* refactor code, add plutil directory, clean import order

* remove old comment

* refine comment

* fix codestyle

* cache sync program, add gputils module, refine model_base unittest

* fix codestyle

* refine sync params cache

* add fetch_value module

* redesign basic class in PARL

* code style fixed

* update yaml's version

* update yaml's version & update code to fix style problem

* add debug message for  function

* delete test code

* rename function: has_fun -> has_func

* fix wrapper of dynamic_lstm cannot support h_0 and c_0 initialization, fix bug of wrapper of dynamic_gru

* use sampling_id of fluid to sampling ids

* remove test simple games unittest, avoid timeout

* change pip source

added test_simple_games

* prelimary implementations of ComputationTask, Algorithm and Model classes

* remove "model_func" from the args of an algorithm

* a clean clone() function for Algorithm and Model

* add use_next_value as a input to learn()

* further re-structure

* added Feedforward and RLAlgorithm classes

* maxid -> argmax

* discrete_distribution -> category_distribution

* category -> categorical

* revisions