Feedforward closed loop learning (FCL) is a learning algorithm which adds flexibility to autonomous agents.
A designer defines an initial behaviour as a reflex and then FCL learns from the reflex to develop new flexible behaviours.
The Python documentation can be obtained with:
import feedforward_closedloop_learning as fcl help(fcl)
The Python API is identical to the C++ API: The documentation can be found here: https://glasgowneuro.github.io/feedforward_closedloop_learning/
The best way to get started is to look at the script in tests_py: https://github.com/glasgowneuro/feedforward_closedloop_learning/tree/master/tests_py
A full application using the Python API is our vizdoom agent: https://github.com/glasgowneuro/fcl_demos
1 maintainer
Release files for feedforward-closedloop-learning 2.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| feedforward_closedloop_learning-2.2.1.tar.gz | 45.0 kB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| feedforward_closedloop_learning-2.2.1-py3.11-win-amd64.egg | Legacy Egg format | - | - | Details |
| feedforward_closedloop_learning-2.2.1-cp311-cp311-win_amd64.whl | CPython 3.11 | CPython 3.11 | Windows x86-64 | Details |
Total release size: 272.4 kB
Release files / feedforward_closedloop_learning-2.2.1.tar.gz
| Download URL | feedforward_closedloop_learning-2.2.1.tar.gz |
|---|---|
| Size | 45.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
47690fb77bab8a46e5a6d1ef9e03018df721198dad5d7493c4fdbe03dfae1a7c
|
|
BLAKE2b-256 checksum How to use checksums |
9a9da0e230b95e30d524f7f59779122469fa5c1f58017d815efd69cea4396200
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.6
|
Release files / feedforward_closedloop_learning-2.2.1-py3.11-win-amd64.egg
| Download URL | feedforward_closedloop_learning-2.2.1-py3.11-win-amd64.egg |
|---|---|
| Size | 115.0 kB |
| Tags | Egg |
|
SHA-256 checksum How to use checksums |
ad6cdceba5145ab0679f126f4de45492c0eb5fb8ea26a96d0ad278546cfc8dea
|
|
BLAKE2b-256 checksum How to use checksums |
f65b6db1536b5563731b89d3865ebeea80d70c90face03c585475ab1bb273d6f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.11.0
|
Release files / feedforward_closedloop_learning-2.2.1-cp311-cp311-win_amd64.whl
| Download URL | feedforward_closedloop_learning-2.2.1-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 112.4 kB |
| Tags | CPython 3.11 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
e55a8c880682519e47fc72494f201eb27be372bbbe4524e861785ff64f83ea06
|
|
BLAKE2b-256 checksum How to use checksums |
c42df224418fceb1c1f6baf7fc8f708a0b874e7e1dc7b7e19d5b492f24a2e134
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.11.0
|
