improb is a Python module for working with imprecise probabilities.

The library supports arbitrary finitely generated conditional lower previsions, belief functions, linear-vacuous mixtures, probability measures, n-monotone lower probabilities, Mobius transforms, and Choquet integration.

Various decision criteria, such as Gamma-maximin, Gamma-maximax, interval dominance, and maximality, are implemented. For sequential decision problems, the library has a convenient interface for constructing decision trees of any size, and has algorithms for solving them by normal form, or by normal form backward induction.

• Download: http://pypi.python.org/pypi/improb/#downloads
• Documentation: http://packages.python.org/improb/
• Development: http://github.com/mcmtroffaes/improb/