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================ Ver. 1.0.2 (2021-12-08)

This module shows how to use SB3 wrapper to train Robothtm

Prerequisites

Please install the following packages to run this examples properly:
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Results

image

After the environment is initiated, the training will run for the specified amount of limits. However, it is noted that there is no visualization available for this environment. The training log is stored in the location specified and a figure plot similar to the figure above will be produced.

YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: ------------------------------------------------------------------------------ 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Training Results of run 0 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: ------------------------------------------------------------------------------ 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: ------------------------------------------------------------------------------ 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Scenario          : RL-Scenario Matrix 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Model             : Agent Smith 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Start time stamp  : YYYY-MM-DD HH:MM:SS.SSSSSS 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- End time stamp    : YYYY-MM-DD HH:MM:SS.SSSSSS 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Duration          : 0:00:59.209252 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Start cycle id    : 0 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- End cycle id      : 11999 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Training cycles   : 12000 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Evaluation cycles : 12500 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Adaptations       : 120 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- High score        : -83.8038799825578 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Results stored in : "C:\Users\%username%\YYYY-MM-DD  HH:MM:SS Training RL" 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Training Episodes : 120 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: -- Evaluations       : 25 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: ------------------------------------------------------------------------------ 
YYYY-MM-DD  HH:MM:SS.SSSSSS  W  Results  RL: ------------------------------------------------------------------------------
In the folder, there should be some files including:
  • agent_actions.csv
  • env_rewards.csv
  • env_states.csv
  • evaluation.csv
  • summary.csv
  • trained model.pkl

Example Code

../../../../../examples/rl/Howto 15 - (RL) Train Robothtm with SB3 Wrapper.py