Saturday, January 4, 2014

Modular intelligence

I am designing a modular framework for artificial intelligence programming. The core system will contain the ontology and module system as well as information about preferences and goals. In this sense the core system will be mostly declarative as it will specify what the agent wants, what classes of entities exist, and what modules are out there and so it will be up to the module system to provide specific knowledge about how to do things.

The modules in the system will be uncertain and context dependent so they will be changing a lot over time. Machine learning algorithms like reinforcement learning and supervised learning should be used to help shape module space. A system with highly advanced machine learning capabilities such as a seed AI could radically transform module space.

Perhaps the most important component of the module space will be the perceptual cortex which will contain all the functionality related to perception and reasoning under uncertainty. An initial perceptual cortex could be built based upon OpenCV as it has many of the perceptual capabilities one could hope for. Another important class of modules are interaction modules which include modules dealing with user interfaces and language processing.

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