Epstein Secrets

Supercompilation 319 18.3.1 Three Aspects of Supercompilation 321 18.3.2 Supercompilation for Goal-Directed Program Modification 322 18.4 Self-Modification via Theorem-Proving 323 A Glossary 325 A.1 List of Specialized Acronyms 325 A.2 Glossary of Specialized Terms 326 References 343 EFTA006

ts xix 18 Advanced Self-Modification: A Possible Path to Superhuman AGI 317 18.1 Introduction 317 18.2 Cognitive Schema Learning 318 18.3 Self-Modification via Supercompilation 319 18.3.1 Three Aspects of Supercompilation 321 18.3.2 Supercompilation for Goal-Directed Program Modification 322 18.4 Self-Modification

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

set of cognitive tools, however, is to create better cognitive tools. One form this sort of tool-building may take is cognitive EFTA00624094 18.3 Self-Modification via Supercompilation 319 schema learning the learning of schemata carrying out cognitive processes in more specialized, context-dependent ways than the general MindAge

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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

in this approach the system is thinking about its MindAgents as black boxes rather than being equipped with full knowledge of their internals. 18.3 Self-Modification via Supercompilation Now we turn to a very different form of advanced self-modification: supercompilation. Super- compilation "merely" enables procedures to run much, mu