Publisher's Synopsis
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.
