An implementation of Non-Axiomatic Reasoning System
Project description
PyNARS
Description
Python implementation of NARS (Non-Axiomatic-Reasoning-System)
Reference:
- OpenNARS 3.0.4,
- The Design Report of OpenNARS 3.1.0
Environments
- Python version: 3.7.10.
- Only tested under this version, however, Python 3.7 and higher versions maybe acceptable.
- OS: Windows 10.
- Only tested under this OS, however, other OSs might be ok.
- Packages Requirements: see
requirements.txt
.- It is noted that the version of the python package
tqdm
should be no higher than 3.1.4, otherwise the color display would be abnormal. This is because of a bug oftqdm
, which leads to conflicts betweensty
andtqdm
and cause unexpected color display ofsty
. However, this constraints is not necessary, i.e., higher version oftqdm
is ok if you don't mind abnormal display occuring. The abnormal case only occurs if you first run PyNARS when SparseLUT (Sparse Look-Up Table) is built.
- It is noted that the version of the python package
Installation
pip install pynars
Instructions
- Copy the file
pynars/config.json
to your workspace-directory. (Optional) - In the workspace-directory, run cmd
python -m pynars.Console
. To execute an*.nal
file, run cmdpython -m pynars.Console <your-file-name.nal>
- Input Narsese in the console, input an positive integer to run a number of cycles, or input a comment which is a string with
'
as the beginning, e.g.' your comment
. - Press
ctrl
+C
to exit.
Contribution
- Fork the repository
- Create Feat_xxx branch
- Commit your code
- Create Pull Request
Note: This document will be imporved in the future.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pynars-0.0.2.tar.gz
(254.8 kB
view details)
File details
Details for the file pynars-0.0.2.tar.gz
.
File metadata
- Download URL: pynars-0.0.2.tar.gz
- Upload date:
- Size: 254.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.0 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2e49c59fa6b2143960685845539dda21d65ce1ce1c40fa59e2e886bc0893420f |
|
MD5 | 02eb76f67d2bcd872386cf86533db5aa |
|
BLAKE2b-256 | e8bd869cc11a85d9d9ae56a5cd7438cfd0bc5e529daeda61460d7a04dddfaa63 |