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Computer System for Adaptive Intelligent Life :: seeks to create a software system that is capable of learning. The project's ultimate goal is to further the ability of software to both adapt to individual users, and to respond their needs.
DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machinelearning algorithms.
It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure.
It can handle highly non-linear dependencies between multivariate random variables.