ABSTRACT
The chapter outlines four different categories of machine learning techniques, such as i) supervised learning, ii) unsupervised learning, iii) reinforcement learning and iv) learning by inductive logic programming. Among the supervised class of machine learning much stress is given to ‘decision tree learning’ and ‘versions space-based learning’. The unsupervised class of learning is introduced briefly with an example classification problem. The reinforcement learning covered in the chapter includes Q-learning and temporal difference learning. The principle of inductive logic programming is introduced from the first principle and illustrated with an example, involving common family relations. The chapter ends with a discussion on the computational theory of learning.
