This directory contains three sample models built with PyIBL, a Python
implementation of a subset of Instance Based Learning Theory,
distributed by Carnegie Mellon University's Dynamic Decision Making
Laboratory. More information, including where to download PyIBL,
is available at http://pyibl.ddmlabl.com.

These versions of these sample models run against version 4.0 of
PyIBL. The examples will not run against version 3.0 or earlier
versions of PyIBL

The file safe_risky.py conatins an iterated, binary choice task,
picking between two choices, one safe and one risky, for three
different likehoods for the risky outcome.

The directory tpt contains an iterated, binary choice task,
consisting of the sixty problems used as part of the Technion
Prediction Tournament in 2008.

The directory dd contains a multi-agent, iterated, binary choice task,
the Diners' Dilemma, again consisting of sixty different problems.
