Synthetic neural modeling: the "Darwin" series of recognition automata
Article Abstract:
Synthetic neural modeling is a multilevel theoretical approach to the problem of understanding the the neuronal bases of adaptive behavior. It uses simultaneous large-scale computer simulations of the nervous system, the phenotype, and the environment of a particular organism to study events and their interactions at these three levels. The simulations are based on physiological and anatomical data. They incorporate detailed models for synaptic modification, for the organization of cells into neuronal groups and larger assemblies, and for the integrated action of multiple cortical layers and brain regions to generate behavior in the context of a particular environment and the unique history of an organism. Synthetic neural modeling takes into account possible evolutionary origins and modes of development of the nervous system, permitting a wide range of psychophysical and behavioral phenomena to be studied within a common framework. The automata discussed here deal first with certain abstract properties of pattern recognition (Darwin 1) and then with categorization and association (Darwin II). The discussion culminates in a description of an automaton with sensory and motor systems and autonomous behavior (Darwin III). The behavior of this automaton is not programmed but results from its encounter with events in its world under constraints of neuronal and synaptic selection. Darwin III exists in an environment of simple two-dimensional shapes moving on a background; its phenotype comprises a sessile 'creature' with an eye and a multijointed arm provided with senses of touch and kinesthesia; its nervous system consists of some 50 interconnected networks containing over 50,000 cells and 620,000 synaptic unctions. By interaction with its environment, Darwin III develops sensorimotor coordination, permitting it to track moving objects with its eye, to reach out and touch objects with its arm, to categorize certain objects according to combinations of visual, tactile, and kinesthetic cues, and to respond to objects based on previous categorizations. These elementary behaviors provide a microcosm in which it is possible to analyze critical problems involving the acquisition and maturation of integrated sensory and motor behavior in animals. (Reprinted by permission of the publisher)
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1990
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Automatic program parallelization
Article Abstract:
An overview of techniques that transform sequential programs into equivalent parallel programs is presented. There are many sequential programs that would be useful to execute on parallel computers, and even if the entire program cannot be translated automatically, parallelizers can make the translation easier for programmers. Parallelizers should allow development of much of the code in such familiar sequential programming languages as Fortran and C, and the techniques could then be applied to other translation problems. Transformations are examined from a generic point of view, and only a few observations are made on how the techniques may be used to generate code for specific machines. An economic model of the target machine should be included in the parallelizer to determine when a particular transformation is profitable or to select one from a collection of possible transformations.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1993
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