Epstein Secrets

Intervals CACM, 26:198-3, 1983. AMOI. J. S. Albus and A. M. Nfeystel. Engineering of Mind: An Introduction to the Science of Intelligent Systems. Wiley and Sons, 2001. Ama85. S. Amari. Differential-geometrical methods in statistics. Lecture notes in statistics, 1985. Ama98. S. Amari. Natural grad

, ImplicationLink, etc.) or a fuzzy value (as in MemberLink, EvaluationLink). • Strong Self-Modification: This is generally used as synonymous with Self-Modification, in a CogPrime context. • Subsymbolic: Involving processing of data using elements that have no correspondence to natural language terms, nor abst

uter, 42(3):90-91, March 2009. ANI01. J. S. Albus and A. Xl. Meystel. Engineering of Mind: An Introduction to the Science of Intelligent Systems. Wiley and Sons, 2001. Ami89. Daniel J. Amit. Modeling brain function - the world of attractor neural networks. Cambridge University Press, New York, USA

cision graph looks like: Input: List L Output: List If ( P1 (L) ) N1(L) Else If ( P2 (L) ) N2 (L) Else If ( Pk (L) ) Nk(L) EFTA00624098 18.4 Self-Modification via Theorem-Proving 323 where the Pi are predicates, and the Ni are schemata corresponding to other nodes of the decision graph (children of the c

Computer, 42(3):90-91, March 2009. AMO1. J. 5S. Albus and A. M. Meystel. Engineering of Mind: An Introduction to the Science of Intelligent Systems. Wiley and Sons, 2001. Ami89. Daniel J. Amit. Modeling brain function — the world of attractor neural networks. Cambridge University Press, New York, USA,

nt decision graphs. The decision graph leading to maximal optimization, may not be the one that leads CogPrime cognition in optimal directions. 18.4 Self-Modification via Theorem-Proving Supercompilation is a potentially very valuable tool for self-modification. If one wants to take an existing schema and graduall