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An alternative computational model for artificial intelligence.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	An alternative computational model for artificial intelligence./
Author:	Stuart, Brian Louis.
Description:	1 online resource (147 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 54-05, Section: B.
Contained By:	Dissertations Abstracts International54-05B.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9798208672976

An alternative computational model for artificial intelligence.
Stuart, Brian Louis.

An alternative computational model for artificial intelligence. - 1 online resource (147 pages)

Source: Dissertations Abstracts International, Volume: 54-05, Section: B.

Thesis (Ph.D.)--Purdue University, 1992.

Includes bibliographical references

One objective of artificial intelligence is to mimic the behavior of natural intelligences, and learning is one of the most inherently intelligent activities. Unfortunately, there has not been much success in emulating the low-level learning of classical conditioning and instrumental learning. A novel model of computation, called the cybernetic automaton, which possesses a number of desirable properties, is presented here. First there exists a learning theorem which states that cybernetic automaton learning is in some sense complete. Then through a series of experiments, it is shown that cybernetic automata exhibit many of the properties of classical conditioning and instrumental learning. Finally, the cybernetic automaton model can be implemented using networks of model neurons which are somewhat biologically plausible. Cybernetic automata represent a new and substantial step toward artificially emulating natural behavior.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798208672976Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

conditioningIndex Terms--Genre/Form:

554714
Electronic books.

An alternative computational model for artificial intelligence.
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504 $a Includes bibliographical references
520 $a One objective of artificial intelligence is to mimic the behavior of natural intelligences, and learning is one of the most inherently intelligent activities. Unfortunately, there has not been much success in emulating the low-level learning of classical conditioning and instrumental learning. A novel model of computation, called the cybernetic automaton, which possesses a number of desirable properties, is presented here. First there exists a learning theorem which states that cybernetic automaton learning is in some sense complete. Then through a series of experiments, it is shown that cybernetic automata exhibit many of the properties of classical conditioning and instrumental learning. Finally, the cybernetic automaton model can be implemented using networks of model neurons which are somewhat biologically plausible. Cybernetic automata represent a new and substantial step toward artificially emulating natural behavior.
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