https://github.com/aria-systems-group/regret_synthesis_toolbox
Source code for Regret synthesis for two-player turn-based game played on graphs - ICRA 22
https://github.com/aria-systems-group/regret_synthesis_toolbox
Science Score: 49.0%
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Repository
Source code for Regret synthesis for two-player turn-based game played on graphs - ICRA 22
Basic Info
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- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 1
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Metadata Files
README.md
Description
This repository contains code for the paper "Let's Collaborate: Regret-based Reactive Synthesis for Robotic Manipulation (ICRA 22)." In this work we introduce algorithms for quantitative regret-based reactive synthesis. We consider resource constrained robotic manipulators that need to interact with a human to achieve a complex task expressed in linear temporal logic. This repository contains the source code to synthesize regret minimizing strategy for the robot operating in a dynamic environment modeled as a two-player turn-based zero-sum game. See the paper for more details.
Table of Contents * Installation * Results * Reference
Installation
Clone the code
- clone this repo with:
bash git clone --recurse-submodules git@github.com:aria-systems-group/regret_synthesis_toolbox.git .
Note: The --recurse-submodule will automatically initialize and update each submodule in the repository. This repository contains following synthesis algorithms.
Supported:
Qualitative Algorithms
- [x]
Adversarial Game (w Permissive strategy synthesis) - [x]
Cooperative Game (w Permissive strategy synthesis) - [ ]
Best-Effort Synthesis(Link)
Quantitative Algorithms
- [x]
Value Iteration (Min-Max and Min-Min) w total Payoff function(Link) - [x]
Finite Trace Regret Synthesis(Link) - [x]
Bounded Human Adversarial Game(Link) - [ ]
Best-Effort Synthesis
For regret-synthesis abstraction and synthesis see the PDDLtoSim repository.
Docker Installation - Creating an Image and Spinning a Container
Make sure you have Docker installed. If not, follow the instructions here.
Docker Commands to build the image
cdinto the root of the projectBuild the image from the Dockerfile
bash
docker build -t <image_name> .
Note: the dot looks for a Dockerfile in the current repository. Then spin an instance of the container by using the following command
bash
docker run -it --name <docker_container_name> <docker image name>
For volume binding
bash
docker run -v <HOST-PATH>:<Container-path>
For example, to volume bind your local directory to the regret_planning folder inside the Docker, use the following command
bash
docker run -it -v $PWD:/root/regret_planning --name <dokcer_container_name> <image_name>
Here <docker_container_name> is any name of your choice and <image_name> is the docker image name from above. -it and -v are flags to run an interactive terminal and volume bind respectively.
Running Gym-Minigrid examples
If you want to record gym-minigrid runs from Wombats library then install ffmpeg tool using the following commands:
bash
apt update && apt upgrade
apt install ffmpeg
To confirm installation, run ffmpeg --version.
Additionally, if you are more used to GUI and would like to edit or attach a container instance to VSCode (Link) then follow the instructions below:
Attaching the remote container to VScode
- Make sure you have the right VS code extensions installed
- install docker extension
- install python extension
- install remote container extension
- Now click on the
Remote Exploretab on the left and attach VScode to a container.
- This will launch a new vs code attached to the container and prompt you to a location to attach to. The default is root, and you can just press enter. Congrats, you have attached your container to VSCode.
Running the code
cd into the regret_planning directory, and run the following command
bash
python3 main.py
Conda Installation - Instructions to create the env for the code
install
spotif you are going to construct a DFA using an LTL formula.change into this repo's directory:
bash cd regret_synthesis_toolboxcreate the
condaenvironment for this library:bash conda env create -f environment.ymlactivate the conda environment:
bash conda activate regret_syn_env
Running the code
cd into the root directory, activate the conda env and run the following command
bash
python3 main.py
Tests
All the tests related scripts are available in the tests/ directory. I use python unittest for testing individual components of my source code. Here are some commands to run the tests:
To run a specific test package:
bash
python3 -m unittest discover -s tests.<directory-name> -bv
To run a specific test script:
bash
python3 -m tests.<directory-name>.<module-nane> -b
To run all tests:
bash
python3 -m unittest -bv
For more details see the tests/README.md. Note, all commands must be run from <root/of/project>.
Spot Troubleshooting notes
You can build spot from source, official git repo or Debain package. If you do source intallation, then run the following command to verify your installation
```bash ltl2tgba --version
```
If your shell reports that ltl2tgba is not found, add $prefix/bin to you $PATH environment variable by using the following command
```bash export PATH=$PATH:/place/with/the/file
```
Spot installs five types of files, in different locations. $prefix refers to the directory that was selected using the --prefix option of configure (the default is /usr/local/).
1) command-line tools go into $prefix/bin/ 2) shared or static libraries (depending on configure options) are installed into $prefix/lib/ 3) Python bindings (if not disabled with --disable-python) typically go into a directory like $prefix/lib/pythonX.Y/site-packages/ where X.Y is the version of Python found during configure. 4) man pages go into $prefix/man 5) header files go into $prefix/include
Please refer to the README file in the tar ball or on their Github page for more details on trouble shooting and installation.
Other known installation issues
Gym-Minigrid related issues
- Due to dependency issues of
Wombatslibrary, bothgymandgym-minigridhave to be of specific version; precisely,gym==0.21.0andgym-minigrid=1.0.2. - When using docker, if you want to visualize minigrid runs, then enable X11 forwarding - Link.
- If you get
'FigureCanvasAgg' object has no attribute 'set_window_title'error when running minigrid examples withrenderflag then you possibly have the wrongmatplotlibversion. Changingmatplotlibversion to 3.5 works. If you already have installedmatplotlibthen use the following command to install the specific version
bash
pip3 install 'matplotlib==3.5' --force-reinstall
Gym-Minigrid installation error
- If you get the following error
python setup.py egg_info did not run successfullywhen installinggym-minigrid=1.0.2then it is likely that you have the wrongsetuptoolsversion. See this link for more info. If you already have installedsetuptoolsthen use the following command to install the specific version.
bash
pip3 install 'setuptools==65.5.0' --force-resinstall
Results
You can find more information at this project link
Citing
If the code is useful in your research, and you would like to acknowledge it, please cite this paper:
@INPROCEEDINGS{muvvala2022regret,
author={Muvvala, Karan and Amorese, Peter and Lahijanian, Morteza},
booktitle={2022 International Conference on Robotics and Automation (ICRA)},
title={Let's Collaborate: Regret-based Reactive Synthesis for Robotic Manipulation},
year={2022},
pages={4340-4346},
doi={10.1109/ICRA46639.2022.9812298}}
Contact
Please contact me if you have questions at :karan.muvvala@colorado.edu
Owner
- Name: ARIA Systems Group
- Login: aria-systems-group
- Kind: organization
- Location: Smead Aerospace Engineering Sciences at the University of Colorado Boulder
- Website: www.AriaSystems.group
- Repositories: 27
- Profile: https://github.com/aria-systems-group
GitHub Events
Total
- Push event: 31
- Create event: 4
Last Year
- Push event: 31
- Create event: 4
Issues and Pull Requests
Last synced: almost 2 years ago
All Time
- Total issues: 3
- Total pull requests: 5
- Average time to close issues: 5 days
- Average time to close pull requests: 25 days
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.4
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 1
- Average time to close issues: 5 days
- Average time to close pull requests: 1 minute
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
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Top Authors
Issue Authors
- MuvvalaKaran (2)
Pull Request Authors
- MuvvalaKaran (3)
- watakandai (2)
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Dependencies
- ubuntu 20.04 build
- bidict
- cloudpickle
- cycler
- docker
- future
- gym
- gym_minigrid
- ipython
- joblib
- matplotlib
- mpmath
- networkx
- numpy
- pandas
- paramiko
- ply
- pybullet
- pydot
- pydot3
- pyglet
- pyperplan
- python-graphviz
- pytz
- pyyaml
- scipy
- shapely
- tqdm