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## Probability driven heuristic nets

Let a probability driven switch be defined as a switch of three input paths and three output paths. The status of the input paths defines a probability for each output path (as to whether it will generate a signal or not.) One output path is linked to one input path, so the results of the switch at time t can affect the switch at time t+1. A switch so constructed can be defined (by the probabilities) to take on the function of the standard logic gates (AND, OR, …) A net constructed of these switches can be “taught” by “reward” and “punish” algorithms to recognize input patterns. A simulation model showed that a repetitive learning algorithm coupled with a base knowledge (where new patterns are learned while continually checking past learned patterns) gives best results as a function of time. A good measure for the level of stability in response is to notice how many probabilities have converged to one or zero. The larger the number, the more stable the net.

Identifer | oai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-2999 |

Date | 25 July 1974 |

Creators | Carter, Lynn Robert |

Publisher | PDXScholar |

Source Sets | Portland State University |

Detected Language | English |

Type | text |

Format | application/pdf |

Source | Dissertations and Theses |

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