Artificial Intelligence and Soft Computing: Behavioral ... - Arteimi.info

13
Machine Learning
Techniques
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 .
13.1 Introduction
Learning is an inherent characteristic of the human beings. By virtue of this,
people, while executing similar tasks, acquire the ability to improve their
performance. This chapter provides an overview of the principle of learning
that can be adhered to machines to improve their performance. Such learning
is usually referred to as ‘machine learning’. Machine learning can be broadly
classified into three categories: i) Supervised learning, ii) Unsupervised
learning and iii) Reinforcement learning. Supervised learning requires a