Epstein Secrets

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

in terms of algorithmic information theory, and quantitatively measured in operational Al systems (Goertzel, Pennachin and Geisweiller, 2014). The CogPrime AGI design comprises an ambitious theoretical framework and practical blueprint for construction of an Artificial General Intelligence system with capab

reinforcement learning mode, to learn small programs that will guide the virtual parrot in achieving its goals (where its goals are managed via the OpenPsi motivational system inside OpenCog, loosely inspired by Joscha Bach's MicroPsi system). • Use of ECAN to learn associational relationships between

in terms of algorithmic information theory, and quantitatively measured in operational Al systems (Goertzel, Pennachin and Geisweiller, 2014). The CogPrime AGI design comprises an ambitious theoretical framework and practical blueprint for construction of an Artificial General Intelligence system with capab

(that recognizes patterns in the hierarchies and passes them to the Atomspace; and imprints patterns from the Atomspace on the hierarchies); and also OpenPsi, a special dynam- ical framework for choosing actions based on motivations. Above the Atomspace we have a host of cognitive processes, which act on t

ll use different processes to fulfill the various roles identified in Figure ?? above. Here we briefly preview the basic cognitive processes that the CogPrime AGI design uses for these roles, and the synergies that exist between these. 8.3.1 Cognitive Processes in CogPrime : a Cognitive Synergy Based Architec