Design and Analysis of Algorithms

Chapter 13

Natural Algorithms — GA, SA, ANN, TS

Objectives

After reading this chapter, you should understand:

• Why do we need Natural Algorithms — Where traditional algorithm design strategies fail
• Evolution
• Mutation and its significance
• Working of a Genetic Algorithm — Why they work, how do they differ from random search
• Simulated Annealing — Principles and applicability
• Artificial Neural Networks — Similarities and differences with Human Brain
• Artificial Neural Networks — Types, principles and applicability
• A single Artificial Neuron — How it processes inputs
• Electronic Implementation of Artificial Neural Networks
• Supervised and Unsupervised learning : Differences
• Training an ANN — The Why and How
• Differences between ANN and Traditional Computing ...