Deep and Modular Neural Networks

In this chapter, we focus on two important areas in neural computation, i.e., deep and modular neural networks, given the fact that both deep and modular neural networks have been among the most powerful machine learning and pattern recognition techniques for complex AI problem solving. We begin by providing a general overview of deep and modular neural networks to describe the general motivation behind such neural architectures and fundamental requirements imposed by complex AI problems. Next, we describe background and motivation, methodologies, major building blocks, and the state-of-the-art hybrid learning strategy in context of deep neural architectures. Then, we describe background and motivation, taxonomy and learning algorithms pertaining to various yet typical modular neural networks in a wide context. Furthermore, we also examine relevant issues and discuss open problems in deep and modular neural network research areas.