On the Predictability of Domain-independent Temporal Planners

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00334344" target="_blank" >RIV/68407700:21230/19:00334344 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/19:10408241

Výsledek na webu

<a href="https://doi.org/10.1111/coin.12211" target="_blank" >https://doi.org/10.1111/coin.12211</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/coin.12211" target="_blank" >10.1111/coin.12211</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On the Predictability of Domain-independent Temporal Planners

Popis výsledku v původním jazyce

Temporal planning is a research discipline that addresses the problem of generating a totally or a partially ordered sequence of actions that transform the environment from some initial state to a desired goal state, while taking into account time constraints and actions' duration. For its ability to describe and address temporal constraints, temporal planning is of critical importance for a wide range of real-world applications. Predicting the performance of temporal planners can lead to significant improvements in the area, as planners can then be combined in order to boost the performance on a given set of problem instances. This paper investigates the predictability of the state-of-the-art temporal planners by introducing a new set of temporal-specific features and exploiting them for generating classification and regression empirical performance models (EPMs) of considered planners. EPMs are also tested with regard to their ability to select the most promising planner for efficiently solving a given temporal planning problem. Our extensive empirical analysis indicates that the introduced set of features allows to generate EPMs that can effectively perform algorithm selection, and the use of EPMs is therefore a promising direction for improving the state of the art of temporal planning, hence fostering the use of planning in real-world applications.

Název v anglickém jazyce

On the Predictability of Domain-independent Temporal Planners

Popis výsledku anglicky

Temporal planning is a research discipline that addresses the problem of generating a totally or a partially ordered sequence of actions that transform the environment from some initial state to a desired goal state, while taking into account time constraints and actions' duration. For its ability to describe and address temporal constraints, temporal planning is of critical importance for a wide range of real-world applications. Predicting the performance of temporal planners can lead to significant improvements in the area, as planners can then be combined in order to boost the performance on a given set of problem instances. This paper investigates the predictability of the state-of-the-art temporal planners by introducing a new set of temporal-specific features and exploiting them for generating classification and regression empirical performance models (EPMs) of considered planners. EPMs are also tested with regard to their ability to select the most promising planner for efficiently solving a given temporal planning problem. Our extensive empirical analysis indicates that the introduced set of features allows to generate EPMs that can effectively perform algorithm selection, and the use of EPMs is therefore a promising direction for improving the state of the art of temporal planning, hence fostering the use of planning in real-world applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Computational Intelligence

ISSN

0824-7935

e-ISSN

1467-8640

Svazek periodika

35

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

29

Strana od-do

745-773

Kód UT WoS článku

000492750300004

EID výsledku v databázi Scopus

2-s2.0-85064605442