I am interested in early material on version space learning and decision-tree induction, because they are relatively easy for humans to understand. They also provide conceptual tools useful to someone interested in cognitive aids.
Given the popularity of neural network models, I think finding books on their history should be easier. I know so little about genetic algorithms, are they part of ML algorithms now, or have they been abandoned? No idea here. I could answer that question with 10 minutes on Wikipedia, though, if my experience follows what is typical.
I am interested in early material on version space learning and decision-tree induction, because they are relatively easy for humans to understand. They also provide conceptual tools useful to someone interested in cognitive aids.
Given the popularity of neural network models, I think finding books on their history should be easier. I know so little about genetic algorithms, are they part of ML algorithms now, or have they been abandoned? No idea here. I could answer that question with 10 minutes on Wikipedia, though, if my experience follows what is typical.