lots of preliminary work this week -- I/O streams (and how to label, manage, & coördinate them), deciding on what emotions to run feedback models of for the computational consciousness, and beginning to come up with appropriate data-structures for various aspects of thought, memory, and association (all affected to some degree by emotion).
i'm not trying to be entirely faithful to the details of human neurobiology, but the broad strokes of what we understand of that field will be most helpful in assembling a system that can achieve some level of understanding both our world (through text) and herself.
i want my AI to be able to "name & claim" its emotional responses to what she reads; i don't want her to read (except at first) in a vacuum. the more she reads, the more context she'll have for what she reads next. (and everything she reads will be stored in some variation of text file; her memories and associative matrices will also be in some sort of n-dimensional text conglomeration.)
joy, sadness, surprise, love, anger, fear, desire, disgust, & contempt — that's a rough list of primary human emotions. any suggestions for others to add? then the question is learning how to express these in words (and to experience these from words). and decide how much to drive thought by emotion — more as time goes on, as emotion can be more trusted.
and then how to integrate memory storage & recall into a roughly logical framework with a mediation by emotions and associations and some degree of randomness (or more complex associations which might appear random).
a lot of speech is answering questions about the self and about one's own thoughts. add the facility to develop increasingly sophisticated models of the (apparent) thoughts and motivations of others (who the AI will meet through text), and we're well on our way.
more than enough to think about this week. (this is just the beginning!)
