OpenCog

OpenCog is a framework for developing AI systems, especially appropriate for integrative multi-algorithm systems, and artificial general intelligence systems. Though much work remains to be done, it currently contains a functional core framework, and a number of cognitive agents at varying levels of completion, some already displaying interesting and useful functionalities alone and in combination.

OpenCog consists of multiple components. At its core is a (hyper-)graph database, the AtomSpace, which is used for representing knowledge and algorithms, providing a surface on which learning and reasoning algorithms are implemented. The AtomSpace consists of an in-RAM database, a "query language" aka "pattern matcher", a (ProLog-like) rule system, including forward and backward chainers, and an evaluator for the internal "programming langauge", Atomese. This language is not really meant to be used by humans (although, defacto, it is) but rather, it is a language for representing knowledge and algorithms, on which (automated) reasoning and learning can be performed. The AtomSpace also provides Scheme (guile) and Python bindings. The AtomSpace is maintained in a separate git repo: http://github.com/opencog/atomspace

For platform dependent instruction on dependencies and building the code, as well as other options for setting up development environments, more details are found on the Building Opencog wiki.