Epstein Secrets

sentation EFTA00624019 EFTA00624020 Chapter 13 Local, Global and Glocal Knowledge Representation Co-authored with Matthew Ikle, Joel Pitt and Rui Liu 13.1 Introduction One of the most powerful metaphors we've found for understanding minds is to view them as networks - i.e. collections of interre

e our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

rolling game al in a minecralt-like environment. In Proc. of RICA 2011, 2011. CP1+10. Ben Goertzel, Joel Pitt, Matthew Ikle, Casein Pennachin, and Rui Liu. Glocal memory: a design principle for artificial brains and minds. Neurocomputing, April 2010. CPPG06. Ben Goertzel, Hugo Pinto, easel° Pennachin

parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. • Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money,

OVERSIGHT_013159 HOUSE_OVERSIGHT_013160 Chapter 13 Local, Global and Glocal Knowledge Representation Co-authored with Matthew Ikle, Joel Pitt and Rui Liu 13.1 Introduction One of the most powerful metaphors we’ve found for understanding minds is to view them as networks — i.e. collections of interrel

ake our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

trolling game ai in a minecraft-like environment. In Proc. of BICA 2011, 2011. GPIt 10. Ben Goertzel, Joel Pitt, Matthew Ikle, Cassio Pennachin, and Rui Liu. Glocal memory: a design principle for artificial brains and minds. Neurocomputing, April 2010. GPPGO06. Ben Goertzel, Hugo Pinto, Cassio Pennachin,

e parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money, ST