Computational Systems

  • George E. Mobus
  • Michael C. Kalton
Part of the Understanding Complex Systems book series (UCS)


Computation is to the processing of data, information, and knowledge, what physical work processes are to material transformations. Indeed computation is a work process of a very special kind in which energy is consumed to transform messages received into usable forms. Here, we will consider several kinds of computational processes and see how they all provide this transformation. Everyone is familiar with the digital computer, which has become one of the most ubiquitous forms of man-made computation. But we will also investigate biological forms of computation, especially, for example, how brains perform computations such as transforming sensory data streams into actions. One especially important use of computation (both in machines and brains) is the construction and running of simulation models.


Conditioned Stimulus Memory Trace Digital Computer Computational Process Binary Number 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Bibliography and Further Reading

  1. Alkon DL (1987) Memory traces in the brain. Cambridge University Press, CambridgeGoogle Scholar
  2. Baars BJ, Gage NM (2007) Cognition, brain, and consciousness. Elsvier AP, New YorkGoogle Scholar
  3. Gilovich T, Griffin D, Kahneman D (eds) (2002) Heuristics and Biases: the psychology of intuitive judgment, Paperbackth edn. Cambridge University Press, New YorkGoogle Scholar
  4. Harel D (1987) The science of computing: exploring the nature and power of algorithms. Addison-Wesley Publishing Company, Inc., New YorkGoogle Scholar
  5. Hyman A (ed) (1989) Science and reform: selected works of Charles Babbage. Cambridge University Press, CambridgeGoogle Scholar
  6. Levine DS, Aparicio M (eds) (1994) Neural networks for knowledge representation and inference. Lawrence Erlbaum Associates, HillsdaleGoogle Scholar
  7. Mobus GE (1994) Toward a theory of learning and representing causal inferences in neural networks.In: Levine and Aparicio (1994), Lawrence Erlbaum Associates, Hillsdale, ch 13Google Scholar
  8. Montague R (2006) Why choose this book: how we make decisions. Dutton, New YorkGoogle Scholar
  9. Patt YN, Patel SJ (2004) Introduction to computing systems: from bits to gates to C & beyond, 2nd edn. McGraw-Hill, New YorkGoogle Scholar
  10. Rumelhart J, McClelland D (1986) Parallel distributed processing: explorations in the microstructure of cognition. MIT, CambridgeGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • George E. Mobus
    • 1
  • Michael C. Kalton
    • 2
  1. 1.Faculty in Computer Science & Systems, Computer Engineering & Systems Institute of TechnologyUniversity of Washington TacomaTacomaUSA
  2. 2.Faculty in Interdisciplinary Arts & SciencesUniversity of Washington TacomaTacomaUSA

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