Epstein Secrets

ceptual, motoric and goal semantic CSDLNs. EFTA00624302 EFTA00624303 Chapter 28 Making DeSTIN Representationally Transparent Co-authored with Itamar Arel 28.1 Introduction In this chapter and the next we describe one particular incarnation of the above ideas on semantic CSDLNs in more depth: the int

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

ligence resulting from the the AGI Roaclmap Workshop held at the University of Knoxville in October 2008 r, which was organized by Ben Goertzel and Itamar Arel. In this list, each broad competency area is listed together with a number of specific competencies sub-areas within its scope: 1. Perception: visi

spatiotemporally hier- archical deep learning system is an effective way to handle representation and learning of low-level sensorimotor knowledge. DeSTIN is one example of a deep learning system of this nature that can be effective in this context. i. One effective way to handle goals is to represent

: Stan Franklin, Juergen Schmidhuber, Marcus Hutter, Kai-Uwe Kuehnberger, Stephen Reed, Blerim Enruli, Kristinn Thorisson, Joscha Bach, Abram Demski, Itamar Arel, Mark Waser, Randal Koene, Paul Rosenbloom, Zhongzhi Shi, Steve Omohundro, Bill Hibbard, Eray Ozkural, Brandon Rohrer, Ben Johnston, John Laird, Shan

a spatiotemporally hier- archical deep learning system is an effective way to handle representation and learning of low-level sensorimotor knowledge. DeSTIN is one example of a deep learning system of this nature that can be effective in this context. i. One effective way to handle goals is to represent

t control systems. e Deep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel [ARC09] and Jeff Hawkins [HB06]. The integrative diagram adopts this as the basic model of the perception and action subsystems of human intelligence

ric, cognitive and linguistic functions. We will achieve this via the creation and real-time utilization of links between the nodes in CogPrime’s and DeSTIN’s internal networks (a topic to be explored in more depth later in this chapter). 6.4 Memory Types and Associated Cognitive Processes in CogPrime N