Soar-Python-Minimum-Working-Example

A minimum working example for using the SOAR cognitive architecture with python for creating an agent that interacts with the environment using SOAR's input-output links.

How to start

On a linux machine:

1) Install java OpenJDK v8

2) Install python 2 and python 3 2.1) Make python 3 your default option by adding this to .bashrc:

alias python=python3

3) Install swig

sudo apt install swig

4) Clone Soar from github:

git clone https://github.com/SoarGroup/Soar.git

5) At Soar's root folder, run python build script:

If you want to use python 2, run this:

python scons/scons.py sml_python

However, if you want to use python 3, run the following:

python2 scons/scons.py sml_python --python=/usr/bin/python3

Build results should be in folder /out

Run hello-world to see if it is working

At a terminal, export LD_LIBRARY_PATH and PYTHONPATH to Soar's code current location, for instance:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/Desktop/Soar/out
export PYTHONPATH=$PYTHONPATH:~/Desktop/Soar/out

An alternative is to copy those lines to the end of .bashrc file, so you don't have to do it every time you open a new terminal.

Run hello world example:

python hello-world.py 

You should see the following:

Hello world
1:    ==>S: S2 (state no-change)  

Run toy-env.py for an example of using IO

Run the toy environmnet example:

python toy-env.py

You should see something like this:

(' ------------- Soar cycle: ', 0, ' ------------- ')
('---> Environment sensed: ', [7, 9])
===> Soar output: 16.000000

===> Soar input: 7.000000 9.000000
1:    O: O2 (initialize-toy-env)
('---> Environment acted:', 0)
(' ------------- Soar cycle: ', 1, ' ------------- ')
('---> Environment sensed: ', [7, 3])
===> Soar output: 10.000000

===> Soar input: 7.000000 3.000000
2:    ==>S: S2 (state no-change)
('---> Environment acted:', 16.0)
(' ------------- Soar cycle: ', 2, ' ------------- ')
('---> Environment sensed: ', [3, 4])
===> Soar output: 7.000000

===> Soar input: 3.000000 4.000000
3:    ==>S: S3 (state no-change)
('---> Environment acted:', 10.0)
soar> 

The goal of this exercise is to show how to use the IO interface and perform a simple cognitive cycle inside a Soar agent. The "toy environment" is just a function that produces two random numbers and receives a single result. This agent receives these numbers through "sensors", add them up, and return them through actuators.

Learn more at

1) Soar Manual http://soar.eecs.umich.edu/downloads/Documentation/SoarManual.pdf

2) Soar Tutorials https://soar.eecs.umich.edu/articles/downloads/soar-suite/228-soar-tutorial-9-6-0

3) Python Interface Example https://soar.eecs.umich.edu/articles/downloads/examples-and-unsupported/183-python-interface-example

4) Python SML Interface file /Soar/build/Core/ClientSMLSWIG/Python/Python_sml_ClientInterface.py

5) pysoarlib https://github.com/amininger/pysoarlib