Artificial Intelligence and Neural Networks

Traditional artificial intelligence and neural networks are generally considered appropriate for solving different types of problems. On the surface these networks appear to be very different, but a growing body of current research is focused on how the strengths of each can be incorporated into the other and built into systems that include the best features of both. This volume presents a critical examination of the key issues, underlying assumptions, and suggestions related to the reconciliation and principled integration of artificial intelligence and neural networks. Examples of this integration for a variety of specific applications are outlined. The text also provides an introduction to the basics of symbol processing, connectionist networks, and their integration.