training networks to explain how they operate.
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“These guys have written a proof that neural networks can’t
therefore no neural networks can do anything interesting
and so forth. Unless these networks are highly
a philosophy of mind book published in 2006; Probabilistic Logic Networks [GIGHO8]
Heterarchical Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282
as does the Probabilistic Logic Networks framework
it can use feedback from DeSTIN’s action and critic networks to further
where Economic Attention Networks (ECAN) are introduced and
using language drawn from Probabilistic Logic Networks (PLN)
its growing networks of computers were largely
because of course networks have layers and structures of
13.4 Knowledge Representation via Attractor Neural Networks 257 N hg = S WikPk k=1,kAi,j 1 Aw = — (pips — hisps — hyivi) 13.4.2 Knowledge Representation via Cell Assemblies Hopfield nets and their ilk play a dual role: as computational algorithms, and as conceptual models of...
5.3 An Architecture Diagram for Human-Like General Intelligence 97 One possible negative reaction to the integrative diagram might be to say that it’s a kind of Frankenstein monster diagram, piecing together aspects of different theories in a way that violates the theoretical no...
networks A machine learning program that can learn how to play an Atari game without any human supervision or hand-crafted engineering (the feat that gave DeepMind 500M from Google) now just takes about 130 lines of Python code. These models do not have interesting motivational...