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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao New Generation Compu...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
New Generation Computing
Article . 1987 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1987
Data sources: zbMATH Open
DBLP
Article . 1987
Data sources: DBLP
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Linearity and plan generation

Authors: Bertram Fronhöfer;

Linearity and plan generation

Abstract

The paper deals with the intuitive linearity concept and its weak points. This concept is commonly used at plan generation using theorem proving in which deduction of a goal statement is proved from the initial situation and rules describing the actions. A typical property of such a concept of linearity is that any literal in a proof is presented only once. Proofs linear in this sense, however, are changing to non-linear ones if the corresponding formulas has been transformed into normal form what is a condition for plan generation by existing theorem provers. The author is trying to suggest such linearity concepts which would overcome troubles connected with the transformation of general formulas into normal forms. As the first step towards an extended linearity concept the so called U-linearity is defined, which allows a multiple occuring of literals and multiple using the rules. To enable multiple connections (according to the connection method used) the concept of C- linearity is introduced, which by some new ``connector literals'' overcomes some of U-linearity limitations. The C-linearity concept is strong enough to generate some types of plans, but to be more applicable, it is required that the state of the world is ``complete with respect to facts and rules'', what is leading to involved new notions of fr- completeness and of numerical stability. This limitation of the world means a reduction of rules to Horn clauses. The last generalization of the linearity concept is called an A-linearity and requires to introduce a further type, so called ``absorbent'' literals. All these generalizations of the linearity concept are illustrated by suitable examples. Finally, a comparison is made to stress the strong points of the author's approach with some classical methods of plan generation such as of Green and STRIPS.

Related Organizations
Keywords

robotics, linearity, Computing methodologies and applications, theorem proving, Theorem proving (deduction, resolution, etc.), plan generation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
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