Motivation, Emotion, and Goal Direction in Neural Networks

Daniel S. Levine, Samuel J. Leven

"...very thought provoking....oriented toward cognitive psychologists, but those with a broad view of neural networks and AI will find it stimulating."—AI Expert"...an interesting and timely book, and I do recommend it. There is a real need to incorporate into network models the actions of neurochemicals in order to form realistic neural network models of emotion and higher level cognitive functioning. This book is one of the first to attempt this synthesis."—Contemporary Psychology

• Contents: Preface. Part I: Theories of Pavlovian Conditioning.M. Aparicio IV, P.N. Strong, Jr., Propagation Controls for True Pavlovian Conditioning. S. Grossberg, N. Schmajuk, D.S. Levine, Associative Learning and Selective Forgetting in a Neural Network Regulated by Reinforcement and Attentive Feedback. E.J. Kehoe, Versatility in Conditioning: A Layered Network Model. P.R. Killeen, Behavioral Geodesics. R. Ricart, Neuromodulatory Mechanisms in Neural Networks and Their Influence on Interstimulus Interval Effects in Pavlovian Conditioning. Part II: Complex Motivational-Cognitive Circuits in the Brain.J.P. Banquet, M. Smith, W. Guenther, Top-Down Processes, Attention, and Motivation in Cognitive Tasks. D. Hestenes, A Neural Network Theory of Manic-Depressive Illness. S.J. Leven, Learned Helplessness, Memory, and the Dynamics of Hope. D.S. Levine, S.J. Leven, P.S. Prueitt, Integration, Disintegration, and the Frontal Lobes. K. Pribram, Familiarity and Novelty: The Contributions of the Limbic Forebrain to Valuation and the Processing of Relevance. Part III: Applications of Goal Direction in Artificial Neural Systems.C.A. Cruz, Knowledge-Representation Networks: Goal Direction in Intelligent Neural Systems. R.L. Dawes, Perfect Memory.