Epstein Secrets

uer, Danielle S. McNamara, Simon Dennis, and Walter Kintsch. Handbook of Latent Semantic Analysis. Psychology Press, 2007. LNOO. George Lakoff and Rafael Nunez. Where Mathematics Comes From. Basic Books, 2000. Loo06. Moshe Looks. Competent Program Evolution. PhD Thesis, Computer Science Department, Wash- i

nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"

nd F. Chao. Staged competence learning in developmental robotics. Adaptive Behavior, 2007. EFTA00624123 348 A Glossary LN00. George Lakoff and Rafael Nunez. Where Mathematics Comes PInsm. Basic Books, 2000. Log07. Robert M. Logan. The Extended Mind. University of Toronto Press. 2007. Loo06. Moshe Loo

nd seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. • PLN: short for Probabilistic Logic Networks • PLN, First-Order: See First-Order hnference • PLN, Higher-Order: See Higher-Order Inference • PLN Rules: A PLN Rule takes as input one or more Atoms (the "premises"

hao. Staged competence learning in developmental robotics. Adaptive Behavior, 2007. HOUSE_OVERSIGHT_013263 348 A Glossary LNOO. George Lakoff and Rafael Nunez. Where Mathematics Comes From. Basic Books, 2000. Log07. Robert M. Logan. The Extended Mind. University of Toronto Press, 2007. Loo06. Moshe Looks.

et and seem relevant to AGI, especially advanced AGI systems capable of strong self-modification. PLN: short for Probabilistic Logic Networks PLN, First-Order: See First-Order Inference PLN, Higher-Order: See Higher-Order Inference PLN Rules: A PLN Rule takes as input one or more Atoms (the “premises”, us