Scientists have modeled a neural network to display
schizophrenic-like language abnormalities by decreasing the information
resilience function, essentially telling the network not to forget as
much of what it’s taught.
From KurzweilAI:
“The researchers taught a series of simple stories to a neural network
programmed to learn and answer questions about narratives, though with
an imperfect memory. When they decreased the program’s ability to
forget, it started giving answers resembling those given by humans
with schizophrenia.
The answers contained dissociated sentences, digressions, and
delusions—at one point the computer claimed responsibility for a
terrorist bombing. Answers also typically included incoherent jumbles
of elements from the various stories it had been taught.”
I don’t think I can even begin to emphasize how much I long for that
source code. A robot programmed just like me! \<3 Oh, and, speaking of
adorable robot-type-entities, thanks to William for reading me that
news article.
[
]
Excuse my incessant xkcd references.
So, now for the serious stuff. I scanned another book today: Linguistic
Fuzzy Logic Methods in Social Sciences by Badredine Arfi. Linguistic
fuzzy logic is used for all sorts of awesome things, including
programming neural networks. This book includes applications to the
Prisoner’s Dilemma in Game Theory, and Skocpol’s Theory of
Revolution!
Linguistic Fuzzy Logic Methods in Social Sciences (click for .pdfs)
Front Cover.pdf
Forewards, Prefaces, and ToC.pdf
Chapter 1 - Linguistic Fuzzy-Logic and Computing with Words.pdf
Chapter 2 - Elements of Linguistic Fuzzy-Logic and Framework.pdf
Chapter 3 - Linguistic Fuzzy-Logic Decision-Making Process.pdf
Chapter 4 - Linguistic Fuzzy-Logic 2x2 Games.pdf
Chapter 5 - Linguistic Fuzzy-Logic Social Game.pdf
Chapter 6 - Linguistic Fuzzy-Logic and Causality.pdf
Chapter 7 - Linguistic Fuzzy-Logic Data Analysis.pdf
Chapter 8 - Conclusion.pdf
References.pdf
Back Cover.pdf
[]: http://www.patternsinthevoid.net/blog/wp-content/uploads/2011/05/lisp.jpg
