Epstein Secrets

g Patterns from DeSTIN States 175 29.3.2 Probabilistic Inference on Mined Hypergraphs 176 29.3.3 Insertion of OpenCog-Learned Predicates into DeSTIN's Pattern Library 177 29.4 Multisensory Integration, and Perception-Action Integration 178 29.4.1 Perception-Action Integration 179 29.4.2 Th

ion Focusing 167 28.6.2 Using Imprecise Probabilities to Guide Visual Attention Focusing 168 28.6.3 Sketch of Application to DeSTIN 168 29 Bridging the Symbolic/Subsymbolic Gap 171 29.1 Introduction 171 29.2 Simplified OpenCog Workflow 173 29.3 Integrating De$TIN and OpenCog 174 29.

e we describe in detail the strategy that would be used to integrate 129 EFTA00624276 130 26 Perceptual and Motor Hierarchies CogPrime with the DeSTIN framework for AGI perception/action (which was described in some detail in Chapter 4 of Part 1). In terms of the integrative cognitive architecture

need to coordinate closely together; or, b. operate largely separately and can be mostly considered as discrete modules 171 EFTA00624318 172 29 Bridging the Symbolic/Subsymbolic Gap In evolutionary, terms, it is clear that subsymbolic intelligence came first, and that most of the human brain is conc

front of the robot, via pinching it between two fingers and then lifting it. In this case, • The visual scene, including the block, is perceived by DeSTIN; and appropriate patterns in various DeSTIN nodes are formed • Predicates corresponding to the distribution of patterns among DeSTIN nodes are acti

a bit, so that it can more easily assess its hand's state visually, and try the optimization-based movement planning again. EFTA00624328 182 29 Bridging the Symbolic/Subsymbolic Gap • Once the robot estimates the goal of gabbing the block has been successfully achieved, it proceeds to the next sub-s