Custom-Design of FDR Encodings: The Case of Red-Black Planning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00350204" target="_blank" >RIV/68407700:21230/21:00350204 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.24963/ijcai.2021/558" target="_blank" >https://doi.org/10.24963/ijcai.2021/558</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.24963/ijcai.2021/558" target="_blank" >10.24963/ijcai.2021/558</a>

Result language

angličtina

Original language name

Custom-Design of FDR Encodings: The Case of Red-Black Planning

Original language description

Classical planning tasks are commonly described in PDDL, while most planning systems operate on a grounded finite-domain representation (FDR). The translation of PDDL into FDR is complex and has a lot of choice points---it involves identifying so called mutex groups---but most systems rely on the translator that comes with Fast Downward. Yet the translation choice points can strongly impact performance. Prior work has considered optimizing FDR encodings in terms of the number of variables produced. Here we go one step further by proposing to custom-design FDR encodings, optimizing the encoding to suit particular planning techniques. We develop such a custom design here for red-black planning, a partial delete relaxation technique. The FDR encoding affects the causal graph and the domain transition graph structures, which govern the tractable fragment of red-black planning and hence affects the respective heuristic function. We develop integer linear programming techniques optimizing the scope of that fragment in the resulting FDR encoding. We empirically show that the performance of red-black planning can be improved through such FDR custom design.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

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

Article name in the collection

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

ISBN

978-0-9992411-9-6

ISSN

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e-ISSN

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Number of pages

8

Pages from-to

4054-4061

Publisher name

International Joint Conferences on Artificial Intelligence Organization

Place of publication

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Event location

Montreal

Event date

Aug 19, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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