Applied Brain Research Inc.

Travis Crncich-DeWolf

Christopher David Eliasmith

Terrence Charles Stewart

Yichuan Tang

Trevor William Bekolay

Feng-Xuan Choo

Daniel Halden Rasmussen

Jean-Jacques Emile Slotine

Daniel Haiden Rasmussen

Methods, systems and apparatus that provide for perceptual, cognitive, and motor behaviors in an integrated system implemented using neural architectures. Components of the system communicate using artificial neurons that implement neural networks. The connections between these networks form representations&#x2014;referred to as semantic pointers&#x2014;which model the various firing patterns of biological neural network connections. Semantic pointers can be thought of as elements of a neural vector space, and can implement a form of abstraction level filtering or compression, in which high-dimensional structures can be abstracted one or more times thereby reducing the number of dimensions needed to represent a particular structure.

Methods and systems for artificial cognition

Methods, systems and methods for designing a system that provides adaptive control and adaptive predictive filtering using nonlinear components. A system design is described that provides an engineered architecture. This architecture defines a core set of network dynamics that carry out specific functions related to control or prediction. The adaptation systems and methods can be applied to limited areas of the system to allow the system to learn to compensate for unmodeled system dynamics and kinematics. Two types of adaptive modules are described which are configured to account for the unmodeled system dynamics and kinematics.

Methods and systems for nonlinear adaptive control and filtering

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Waterloo, Canada

Travis Crncich-DeWolf