Artificial Intelligence: Belief Networks: Software

A tool for constructing and testing Bayesian networks.

Bayesian network laboratory producing a broad set of tools for structure learning, analysis, adaptive questionnaires, and dynamic Bayesian networks

CISpace tools for learning about belief networks: a set of Java applets and example networks.

Able to learn Bayesian Belief Networks from (possibly incomplete) databases. Algorithm based on the Bound and Collapse estimation method.

Kevin Murphy's MATLAB toolbox - supports dynamic BNs, decision networks, many exact and approximate inference algorithms, parameter estimation, and structure learning

Open-source suite of software tools for research and development using graphical models of probability, published by Kansas State University Laboratory for Knowledge Discovery in Databases (KDD)

Very generic and free (LGPL) Belief Network Framework in C++ - supports a broad range of knowledge and dependency types for network variables and clusters of variables

System based on Jie Cheng's three-phase belief network construction algorithm. Includes a wizard-like user interface and a belief network construction engine.

Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods.

Develops and exploits proprietary Relational Bayesian Modeling (RBM) technology and applications that provide real-time, actionable results from large amounts of dynamic, multi-faceted, ambiguous information.