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Wyszukujesz frazę "linear complexity" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
On transformation of STRIPS planning to linear programming
Autorzy:
Galuszka, A.
Powiązania:
https://bibliotekanauki.pl/articles/229963.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
planning
problem solving
block world
uncertainty
linear programming
computational complexity
Opis:
STRIPS language is a convenient representation for artificial intelligence planning problems. Planning is a task of coming up with a sequence of actions that will achieve a goal. In this work a heuristic of polynomial transformation of STRIPS planning problem to linear programming problem (LP) is presented. This is done because planning problems are hard computational problems (PSPACE- complete in general case) and LP problems are known to be computational easy. Representation of STRIPS planning as a set of equalities and inequalities based on the transformation is also proposed. The exemplary simulation shows the computational efficiency of solving planning problem with proposed transformation.
Źródło:
Archives of Control Sciences; 2011, 21, 3; 243-267
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On transformation of conditional, conformant and parallel planning to linear programming
Autorzy:
Galuszka, Adam
Probierz, Eryka
Powiązania:
https://bibliotekanauki.pl/articles/1409385.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
planning
conformant planning
conditional planning
parallel planning
uncertainty
linear programming
computational complexity
Opis:
Classical planning in Artificial Intelligence is a computationally expensive problem of finding a sequence of actions that transforms a given initial state of the problem to a desired goal situation. Lack of information about the initial state leads to conditional and conformant planning that is more difficult than classical one. A parallel plan is the plan in which some actions can be executed in parallel, usually leading to decrease of the plan execution time but increase of the difficulty of finding the plan. This paper is focused on three planning problems which are computationally difficult: conditional, conformant and parallel conformant. To avoid these difficulties a set of transformations to Linear Programming Problem (LPP), illustrated by examples, is proposed. The results show that solving LPP corresponding to the planning problem can be computationally easier than solving the planning problem by exploring the problem state space. The cost is that not always the LPP solution can be interpreted directly as a plan.
Źródło:
Archives of Control Sciences; 2021, 31, 2; 375-399
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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