Conformant Planning with Static Causal Laws and Negation as Failure: Decomposition of the ASP Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00227821" target="_blank" >RIV/68407700:21230/14:00227821 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Conformant Planning with Static Causal Laws and Negation as Failure: Decomposition of the ASP Approach

Popis výsledku v původním jazyce

In recent years, we have seen a few attempts to use the Answer Set Programming (ASP) to solve the problem of conformant planning with the support for causal laws and negation as failure. Typically, the whole planning domain is encoded into a large ASP meta-program expressing what holds and which actions should be executed in all the time steps of a resulting plan. Answer sets of this meta-program then represent all the possible plans. Since the complexity of answer set computation is exponential in sizeof input, we propose a technique of dividing it into several smaller meta-programs - one for every state transition. Actual plan finding can then be outsourced to a graph-search algorithm. This method increases the performance of planning with ASP semantics and allows us to produce considerably longer plans. After discussing the worst-case complexity of both approaches, we introduce the prototype ASP planner GRASP that employs our suggested technique and provide the experimental compari

Název v anglickém jazyce

Conformant Planning with Static Causal Laws and Negation as Failure: Decomposition of the ASP Approach

Popis výsledku anglicky

In recent years, we have seen a few attempts to use the Answer Set Programming (ASP) to solve the problem of conformant planning with the support for causal laws and negation as failure. Typically, the whole planning domain is encoded into a large ASP meta-program expressing what holds and which actions should be executed in all the time steps of a resulting plan. Answer sets of this meta-program then represent all the possible plans. Since the complexity of answer set computation is exponential in sizeof input, we propose a technique of dividing it into several smaller meta-programs - one for every state transition. Actual plan finding can then be outsourced to a graph-search algorithm. This method increases the performance of planning with ASP semantics and allows us to produce considerably longer plans. After discussing the worst-case complexity of both approaches, we introduce the prototype ASP planner GRASP that employs our suggested technique and provide the experimental compari

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Artificial Intelligence

ISSN

0974-0635

e-ISSN

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Svazek periodika

12

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

IN - Indická republika

Počet stran výsledku

12

Strana od-do

48-59

Kód UT WoS článku

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EID výsledku v databázi Scopus

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