The relations between implicit parallelism and artifical intelligence

Peng Wang, Qianhe Xie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Implicit parallelism exists in a lot of intelligence algorithms. It is the causation of parallel search ability in results space of some algorithms. Implicit parallelism of algorithm is analyzed by physical theory and find that the uncertainty and high entropy state of algorithm are the root of the implicit parallelism. But the uncertainty is the cost of implicit parallelism. In other words, if an algorithm wants to get high level implicit parallel computing ability it must reduce the computing precision. For an intelligence algorithm the apriori knowledge decides the search direction in results space and the implicit parallelism provides the high speed parallel search ability. According to this we can increase the apriori knowledge and implicit parallelism to get the high level intelligence algorithm. Correct search direction plus implicit parallelism is artificial intelligence. The implicit parallelism and the prior knowledge together form the two elements of intelligence algorithm: speed and direction.

Original languageEnglish
Title of host publication2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop Proceedings, KAM 2008
Pages506-509
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop, KAM 2008 - Wuhan, China
Duration: 21 Dec 200822 Dec 2008

Publication series

Name2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop Proceedings, KAM 2008

Conference

Conference2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop, KAM 2008
Country/TerritoryChina
CityWuhan
Period21/12/0822/12/08

Keywords

  • Apriori knowledge
  • Entropy
  • High entropy state
  • Implicit parallelism
  • Uncertainty

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