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Implementation of Li's Learning to Optimize paper using Pytorch

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Code for Learning to Optimize

This is a Python re-implementation of the method described in our paper, which can be found at https://arxiv.org/abs/1606.01885

It is based on the Guided Policy Search implementation (https://github.com/cbfinn/gps). 

Copyright (C) 2017    Ke Li, Jitendra Malik

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.

===========================================================================================================================================

Run compile_proto.sh first before running run_lto.sh

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