Epstein Secrets

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e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Con

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

ed to reach a more orthogonal set. A straightfor- ward way to do this is to exploit the reduction to nor

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

e, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concr

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