Request Confirmation Networks in MicroPsi 2

摘要

To combine neural learning with the sequential detection of hierarchies of sensory features, and to facilitate planning and script execution, we propose Request Confirmation Networks (ReCoNs). ReCoNs are spreading activation networks with units that contain an activation and a state, and are connected by typed directed links that indicate partonomic relations and spatial or temporal succession. By passing activation along the links, ReCoNs can perform both neural computations and controlled script execution. We demonstrate the application of ReCoNs in the context of performing simple arithmetic, based on camera images of mathematical expressions.