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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This sample of code implements the "Learning Dexterous In-Hand Manipulation" paper [1] using the PyRoboLearn framework.
We use the same factors as described in the paper; i.e. the same robotic platform, same states and actions,
same policies, same rewards (and coefficients), same learning algorithm with same hyperparameters, and so on.
Reference:
[1] "Learning Dexterous In-Hand Manipulation", OpenAI et al., 2019 (https://arxiv.org/abs/1808.00177)
"""
import time
from itertools import count
import pyrobolearn as prl
from env import Openai2018LearningEnv
# create environment (create world, states, rewards, actions)
environment = Openai2018LearningEnv()
# run environment
for t in count():
environment.step()
time.sleep(1./240)
# create policy
# create algo