ReadME add description on BINDS lab

README.md

@@ -1,8 +1,10 @@
 # BindsNET
 
-Python package used for simulating spiking neural networks (SNNs) in [PyTorch](http://pytorch.org/).
+A Python package used for simulating spiking neural networks (SNNs) using [PyTorch](http://pytorch.org/) GPU functionality.
 
-We are interested in applying SNNs to machine learning (ML) and reinforcement learning (RL) problems, but the code (especially the core `network` functionality for building and simulating SNNs) can be used for any purpose.
+BindsNET is a spiking neural network simulation software, a critical component enabling the modeling of neural systems and the development of biologically inspired algorithms in the machine learning domain.
+
+This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the [Biologically Inspired Neural & Dynamical Systems (BINDS) lab](http://binds.cs.umass.edu/). 
 
 [![Build Status](https://travis-ci.com/Hananel-Hazan/bindsnet.svg?token=trym5Uzx1rs9Ez2yENEF&branch=master)](https://travis-ci.com/Hananel-Hazan/bindsnet)
 
@@ -12,19 +14,27 @@ We are interested in applying SNNs to machine learning (ML) and reinforcement le
 
 ## Setting things up
 
-To build the `bindsnet` package from source, change directory to the top level of this project and issue
+BindsNET is available on PyPI. Issue
+
+```
+pip install bindsnet
+```
+
+to get the most recent stable release. Or, to build the `bindsnet` package from source, clone the GitHub repository, change directory to the top level of this project, and issue
 
 ```
 pip install .
 ```
 
-Or, to install in editable mode (allows modification of package with re-installing):
+Or, to install in editable mode (allows modification of package without re-installing):
 
 ```
 pip install -e .
 ```
 
-PyPI support (`pip install bindsnet`) *hopefully* coming soon.
+To install the packages necessary to interface with the [OpenAI gym RL environments library](https://github.com/openai/gym), follow their instructions for installing the packages needed to run the RL environments simulator (on Linux / MacOS).
+
+## Getting started
 
 To run a near-replication of the SNN from [this paper](https://www.frontiersin.org/articles/10.3389/fncom.2015.00099/full#), issue
 
@@ -42,9 +52,11 @@ A number of other examples are available in the `examples` directory that are me
 Issue the following to run the tests:
 
 ```
-python -m pytest test
+python -m pytest test/
 ```
 
+Some tests will fail if Open AI `gym` is not installed on your machine.
+
 ## Background
 
 The simulation of biologically plausible spiking neuron dynamics can be challenging. It is typically done by solving ordinary differential equations (ODEs) which describe said dynamics. PyTorch does not explicitly support the solution of differential equations (as opposed to [`brian2`](https://github.com/brian-team/brian2), for example), but we can convert the ODEs defining the dynamics into difference equations and solve them at regular, short intervals (a `dt` on the order of 1 millisecond) as an approximation. Of course, under the hood, packages like `brian2` are doing the same thing. Doing this in [`PyTorch`](http://pytorch.org/) is exciting for a few reasons:
@@ -63,8 +75,11 @@ We have provided some simple starter scripts for doing unsupervised learning (le
 
 - Daniel Saunders ([email](mailto:djsaunde@cs.umass.edu))
 
-- Hananel Hazan ([email](mailto:hananel@hazan.org.il))
+- Hananel Hazan ([email](mailto:hananel@cs.umass.edu))
 
 - Darpan Sanghavi ([email](mailto:dsanghavi@cs.umass.edu))
 
 - Hassaan Khan ([email](mailto:hqkhan@umass.edu))
+
+## License
+GNU Affero General Public License v3.0