Epstein Secrets

th to Superhuman AGI Fide implication Dog Dog implication NIRO (.1) !lido a Nice Implication PLN Deduction Rule harchtoclyd on C • • or Python) O PLN INFERENCE DeClarative representation of PLN deduction rule in atomspace .... •. • PIA le a set a Schema Node that can modify the

hich data and procedure are explicitly identical, and there is just one new active data structure in place of the distinction between AtomSpace and MindAgents Where on this continuum does the "mere learning" end and the "real self-modification" start? In this chapter we consider some mechanisms for "adva

ilation 319 schema learning the learning of schemata carrying out cognitive processes in more specialized, context-dependent ways than the general MindAgents do. Eventually, once a CogPrime instance becomes sufficiently complex and advanced, these cognitive schema may replace the MindAgents altogether, l

0 18 Advanced Self-Modification: A Possible Path to Superhuman AGI Fido implication — Dog implication Nice PLN Deduction Rule (hard-coded in C++ or Python) ; (8) Fido. : —— > Nice implication - implication i icati N PLN is a set Fido P = Dog Dog bal ee Nice of Schema Nodes that can modify the Atomspac

mpilation 319 schema learning the learning of schemata carrying out cognitive processes in more specialized, context-dependent ways than the general MindAgents do. Eventually, once a CogPrime instance becomes sufficiently complex and advanced, these cognitive schema may replace the MindAgents altogether, lea

which data and procedure are explicitly identical, and there is just one new active data structure in place of the distinction between AtomSpace and MindAgents Where on this continuum does the "mere learning" end and the "real self-modification" start? In this chapter we consider some mechanisms for "advan

basic CogPrime terminology. Also, OpenCog and OpenCogPrime are open-source, so the reader who wishes to dig into the source code (mostly C++, some Python and Scheme) is welcome to; directions to find the code are on the opencog . org website. 3 EFTA00624150 4 19 The OpenCog Framework Level of Ab

Agent migration, and machines joining or leaving the CogPrime cluster. So, at the Unit level, attention allocation in CogPrime has two aspects: how MindAgents and Tasks receive attention from CogPrime, and how Atoms receive attention from different MindAgents and Tasks. The topic of this Section is the fo

nalty function. In the current CogPrime codebase, the algorithm in charge of calibrating the parameters of the penalty function has been written in Python. It takes in input the log of the imitation learning engine that contains the score, the size, the penalty and the fitness of all candidates explor

to Atoms with more impor- tance, and hence creates an evolutionary, dynamic with importance as the fitness criterion and the whole constellation of MindAgents as the novelty-generation mechanism. However, MOSES explicitly embodies evolutionary dynamics for the learning of new patterns and procedures that

history. In the standard CogPrinte notation as introduced formally in Chapter 20 (where indentation has function-argument syntax similar to that in Python, and relationship types are prepended to their relata without parentheses), for the case C is declarative this would be written as PredictiveExtens

gh STI., which rapidly decreases in meet cases local workspaces bubbles of interlinked Atoms with moderate impor- tance, focused on by a subset of MindAgents (defined in Chapter 19 of Part 2) for a period of time perceptual associative memory HebbianLinks in the AT sensory memory spaceserver/timeserve

s history. In the standard CogPrime notation as introduced formally in Chapter 20 (where indentation has function-argument syntax similar to that in Python, and relationship types are prepended to their relata without parentheses), for the case C is declarative this would be written as PredictiveExtensi

high STI, which rapidly decreases in most cases ocal workspaces bubbles of interlinked Atoms with moderate impor- ance, focused on by a subset of MindAgents (defined in Chapter 19 of Part 2) for a period of time perceptual associative memory |HebbianLinks in the AT sensory memory spaceserver /timeserver