Part VI of the AIMA book covers learning and various techniques on agents can learn. The material covers Learning from Observations, Neural Networks, Reinforcement Learning, and Knowledge in Learning. In the second edition, the chapter in Neural Networks is replaced with Statistical Learning Methods.
I read Chapter 18 of the AIMA book called Learning from Observations. The Chapter focuses on decision trees and decision lists as some computational learning theory. The main classification algorithm is the ID3 algorithm for classifying examples and generating decision trees. The ID3 algorithm is based on Hunt’s Concept Learning System (CLS). The ID3 algorithm uses information theory for obtaining the decision tree covering most the examples. I have studied the ID3 algorithm quite extensively since the original application was to classify the winning position in the king and rook versus the king and knight endgame (Quinlan 1983).
