1. 18 3月, 2020 1 次提交
    • H
      LiftSim A2C baseline (#209) · 6b70b81d
      Hongsheng Zeng 提交于
      * liftsim a2c baseline
      
      * update readme
      
      * compatible with different os
      
      * empty
      
      * refine comments
      
      * remove unnecessary assertion; add tensorboard guide
      
      * remove unnecessary assertion
      
      * update parl dependence of A2C
      6b70b81d
  2. 02 8月, 2019 1 次提交
    • F
      first pr (#113) · b29a1ec1
      fuyw 提交于
      * first pr
      
      * start a worker when the master is started.
      
      * First PR & Fix logger bugs.
      
      * update docs for a2c, impala and ga3c
      
      * update doc
      
      * yapf modification
      
      * update logger
      
      * yapf correct
      
      * yapf
      
      * setup.py
      
      * old setup.py
      
      * worker 86
      b29a1ec1
  3. 18 6月, 2019 1 次提交
  4. 15 4月, 2019 1 次提交
    • H
      A2C example (#62) · 39846831
      Hongsheng Zeng 提交于
      * 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
      39846831
  5. 08 4月, 2019 1 次提交
    • H
      implement of IMPALA with the newest parallel design (#60) · b28289ac
      Hongsheng Zeng 提交于
      * 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
      b28289ac