Epstein Secrets

, dealing with with a variety of general conceptual issues related to the engineering of advanced AGI, as well as presenting a brief overview of the CogPrime design for Artificial General Intelligence. Now here in Part 2 we plunge deep into the nitty-gritty, and describe the multiple aspects of the CogPr

heritance A Similarity A B Note that here the symmetry or otherwise of the link is not implicit in the notation. Similar- ityLinks are symmetrical, InheritanceLinks are not. When this distinction is necessary, it will be explicitly made. WIKISOURCE:FunctionNotation 20.3 Representing Functions and Predicates Sc

cedure Learning as Program Learning 30.1 Introduction Broadly speaking, the learning of predicates and schemata (executable procedures) is done in CogPrime via a number of different methods, including for example PLN inference and concept predicatization (to be discussed in later chapters). Most of thes

d B are characterized by relationships of the form Member C A, Member D B, etc. It is easy to see that, in the crisp case, where all MemberLinks and InheritanceLinks have strength 0 or 1, FOPLN reduces to standard propositional logic. Where inheritance is crisp but membership isn't, FOPLN reduces to higher-order

what this "tuning" should involve - namely, making a system possessing mind-state sequences that correspond meaningfully to world-state sequences. CogPrime's overall design and particular cognitive processes are reasonably well interpreted as an attempt to achieve this for everyday human goals and envir

sorimotor network will naturally possess hierarchical conceptual relationships, and will thus naturally grow hier- archical links between them (e.g. InheritanceLinks and IntensionalinheritanceLinks via PLN, AsymmetricHebbianLinks via ECAN). EFTA00624057 15 Emergent Networks of Intelligence artefact Fig. 15.2

ut what this "tuning" should involve — namely, making a system possessing mind-state sequences that correspond meaningfully to world-state sequences. CogPrime’s overall design and particular cognitive processes are reasonably well interpreted as an attempt to achieve this for everyday human goals and enviro

nsorimotor network will naturally possess hierarchical conceptual relationships, and will thus naturally grow hier- archical links between them (e.g. InheritanceLinks and IntensionalInheritanceLinks via PLN, AsymmetricHebbianLinks via ECAN). HOUSE_OVERSIGHT_013197 282 15 Emergent Networks of Intelligence Fig. 15