Skip to content

Latest commit

 

History

History
32 lines (26 loc) · 1.73 KB

README.md

File metadata and controls

32 lines (26 loc) · 1.73 KB

irl-patrolling

Generate patrolling paths via Inverse Reinforcement Learning

Project consists of a MATLAB component for Inverse Reinforcement Learning of patrolling paths generated using the Open Motion Planning Library, and a Python script to visualize the polcies as a new trajectory.

References

Modification of Sergey Levein's work, found at: https://graphics.stanford.edu/projects/gpirl/ Copyright (c) 2011, Sergey Levine All rights reserved.

This software is made available under the Creative Commons Attribution-Noncommercial License, viewable at http://creativecommons.org/licenses/by-nc/3.0/. You are free to use, copy, modify, and re-distribute the work. However, you must attribute any re-distribution or adaptation in the manner specified below, and you may not use this work for commercial purposes without the permission of the author.

Any re-distribution or adaptation of this work must contain the author's name (Sergey Levine) and a link to the software's original webpage.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.