Systems with Learning and Memory Abilities

A comparison of the properties of various systems which have learning and memory abilities, this book is of a multidisciplinary nature. Artificial Intelligence specialists, mathematicians, physicists, biochemists, neuroscientists and psychologists are among the contributors. Divided into five sections, the first considers learning and memory at the behavioral level, while the second is a continuation of this, dealing with neural bases. The third also illustrates a continuity, that between neurobiology and ``basic biology''. The last two sections are both concerned with models of learning and memory, one inspired or constrained mainly by biological facts and the other by physics.

Table of Contents:
Learning and Memory at the Behavioral Level. Visual Memory in Bees (J.L. Gould). A Cognitive Action Theory of Learning (H.L. Roitblat). Developmental Change in Learning and Memory: Infantile Disposition for Unitization (N.E. Spear). Symbolic and Sub-Symbolic Models of Memory (G. Tiberghien). Neural Bases. Pharmacological Studies and Models of Learning and Memory (G. Chapouthier). A View on the Memory System of the Mammalian Brain (J. Delacour). The Organization of Memories into ``Files'' (I. Izquierdo et al.). Neuronal Organization of Memory Functions in Animals and Humans (R.P. Kesner). Long Term Memory Processing in the Human Brain: On the Influence of Individual Variations (H.J. Markowitsch). Mind and Memory: Between Metaphor and Molecule (S. Rose). EEG Research of Neural Dynamics: Implications for Models of Learning and Memory (C.A. Skarda, W.J. Freeman). Learning, Memory and Basic Biology. Conditioning of Immune Responses (R. Dantzer, F. Crestani). Learning Induced Gene Stimulation: The RNA Hypothesis for Learning and Memory (H. Hyden, A. Cupello). Molecular Memory and Sensing Chemical Signals by Enzymes (J. Ricard et al.). Learning and Memory in the Immune System: ``Know Your Self'' (M. Seman). Biology-Oriented Models. A Learning Theory Using the Hierarchic Regulators Model (P. Anizan). The Use of Neural Models Exhibiting Memory Domains Can Account for Complex Brain Phenomena (P. Anninos et al.). Correlation Principle and Physiological Interpretation of Synaptic Efficacy (G. Chauvet). Neural Networks and Visual Pattern Recognition (K. Fukushima). Mesoscales in Neocortex and in C 3 Systems (L. Ingber). Trion Model of Cortical Organization and the Search for the Code of Short-Term Memory and of Information Processing (G.L. Shaw et al.). Learning by Selection Using Energy Functions (P. Stolorz, G.W. Hoffmann). Problems in Modelling the Nervous System: Cerebellar Capacity for Pattern Recognition (J.B. Willis). Physico-Mathematical Models. Neural Networks: Learning Rules and Memory Capacity (M.B. Gordon). Independent Components Analysis in Neural Networks (J. Herault, C. Jutten). Event Horizons in Associationist Models of Memory (B.A. Huberman). Neural Networks with Self Organization (J.C.S. Levy, D. Mercier). Spin Models of Neural Networks (W.A. Little). Magnetic Domains for Memories (I.B. Puchalska, G.A. Jones). Cellular Automata and Models of Memory (P. Rujan). A Multitude of Phases in the ANNNI Model (W. Selke).