Neural Stimulus Representations and Computational Learning  Models
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BARTO                                                                                                                                                           Learning in animals involves complex brain processes that                       integrate sensory information into a coordinated set of actions:                It is something that animals do very well, but man-made thinking                machines (computers) do rather poorly by comparison.  In order to               improve computer performance, many scientists and engineers have                turned to the brain for theoretical insights into the processes                 of learning.  These insights, when applied to computer                          technology, have become increasingly important in applications                  ranging from industrial robotics to process control.                                                                                                            Studies of animal behavior, dating from the early years of this                 century, have provided a rich scientific literature for                         evaluating theories of learning.  These are normally expressed in               terms of mathematical relationships between environmental events                (stimuli) and actions (responses).  State-of-the-art learning                   theories are known as "real-time computational learning models"                 because they can readily be translated into computer programs for               application to technology.                                                                                                                                      Drs. Moore and Barto are using a well-characterized associative                 learning paradigm (that is, learning that one event preceeds                    another event), classical conditioning of the nictitating                       membrane response in the intact rabbit.  This preparation serves                them as a laboratory benchmark for evaluating their recently                    proposed mathematical learning model, and holds much promise both               for clafifying brain processes underlying learning, and for                     enhancing and advancing computer technology.                                                                                                                    The ultimate goal of this research is to discover how information               is processed so efficiently by the brain.  These investigators                  will incorporate this knowledge into a mathematical model, in a                 way that best describes the relationship between a specific                     behavior and the brain mechanisms underlying that behavior.  This               new information can then be applied directly to information                     acquisition by the latest generation of computer systems.
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{'Code': '1161', 'Text': 'NEUROBIOLO OF LEARNING & MEMOR'}
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