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It is the goal of several sciences to construct models of behavior and cognition. Two fundamental questions for all such endeavors are: What mechanisms are required to support cognitive processes in an animal or a robot. How do such mechanisms interact with each other? This book is an attempt to study these questions within the field of behavior-based systems and artificial neural networks. The overall task will be to construct complete, artificial nervous systems for simulated artificial creatures. This enterprise will take as its starting point studies made of biological systems within ethology and animal learning theory. We will also consider many ideas from neurobiology and psychology, as well as from behavior-based robotics and control theory. All these areas have valuable insights to contribute to the understanding of cognition. Ethology has stressed the importance of innate fixed-action patterns, or instincts, in the explanation of behavior. Another significant contribution is the demand that behavior should be studied in the natural habitat of an animal. This leads to a view of behavior and cognition which is very different from the one suggested by animal learning theory. This latter theory attempts to understand the basis of learning by observing the behavior of animals in laboratory experiments. It suggests a view of cognition that is complementary to that offered by ethology, since it stresses the role of learning rather than innate mechanisms. However, as more empirical data become available, the models in both ethology and animal learning theory gradually converge on what may become a substantially more unified theory of animal learning …