Metadata-Version: 2.1
Name: pyibl
Version: 4.1.3
Summary: A Python implementation of a subset of Instance Based Learning Theory
Home-page: http://pyibl.ddmlab.com/
Author: Dynamic Decision Making Laboratory of Carnegie Mellon University
Author-email: dfm2@cmu.edu
License: Free for research purposes
Description: PyIBL is a Python implementation of a subset of Instance Based Learning Theory
        (IBLT) (Cleotilde Gonzalez, Javier F. Lerch and Christian Lebiere (2003),
        Instance-based learning in dynamic decision making, Cognitive Science, 27,
        591-635. DOI: 10.1016/S0364-0213(03)00031-4). It is made and distributed by
        the Dynamic Decision Making Laboratory of Carnegie Mellon University for
        making computational cognitive models supporting research in how people make
        decisions in dynamic environments.
        
        PyIBL requires Python version 3.6 or later. PyIBL also works in recent
        versions of PyPy.
        
        For further information, including the documentation and instructions for
        downloading the latest version, see the
        [online documentation](http://pyibl.ddmlab.com).
        
        PyIBL is copyright 2014-2021 by Carnegie Mellon University. It may be
        freely used, and modified, but only for research purposes.
        
Platform: any
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
