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Unsupervised Agent Based Artificial Intelligence Learning System (Ref # WFU 11-62)
Wake Forest Innovations United States flag United States
Abstract ID:
The Agent Based Brain Model (ABBM) is an artificial intelligence system that mimics the problem-solving pattern of the human brain.
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Value Proposition

Current artificial intelligence systems are developed based on previously learned or programmed responses to specific stimuli that are different from the methods used by the human brain. These systems preclude the use of emergent behavior in problem solving. Researchers have developed a device with a form of strong artificial intelligence that has demonstrated the ability to solve computational problems and exhibit emergent behaviors. This computer-based system remembers the behaviors that it has produced before and the benefits of those behaviors, while being able to interact within an environment.

Invention Summary

The Agent Based Brain Model, or ABBM, uses brain connectivity information generated from imaging modalities such as functional magnetic resonance imaging (fMRI) that enable the interference of functional interdependence between brain regions. Functional connectivity is used in establishing brain networks comprising the links between specific brain regions called nodes. Interactions between various nodes reflect human brain architecture. This innovation inputs human imaging data into the system and results in a computer-based artificial intelligence system that has the potential to produce emergent solutions in a fashion similar to the human brain.

Competitive Benefits

Type of Business Relationship Sought
Exclusive by Fields Licensing Arrangement
Possibility of a parallel Sponsored Research Agreement
Last Updated Jan 2014
Technology Type
Phase of Development PRECLINICAL

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