Planning with Critical Section Macros: Theory and Practice
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00363583" target="_blank" >RIV/68407700:21230/22:00363583 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1613/JAIR.1.13269" target="_blank" >https://doi.org/10.1613/JAIR.1.13269</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1613/JAIR.1.13269" target="_blank" >10.1613/JAIR.1.13269</a>
Alternative languages
Result language
angličtina
Original language name
Planning with Critical Section Macros: Theory and Practice
Original language description
Macro-operators (macros) are a well-known technique for enhancing performance of planning engines by providing "short-cuts" in the state space. Existing macro learning systems usually generate macros by considering most frequent action sequences in training plans. Unfortunately, frequent action sequences might not capture meaningful activities as a whole, leading to a limited beneficial impact for the planning process.In this paper, inspired by resource locking in critical sections in parallel computing, we propose a technique that generates macros able to capture whole activities in which limited resources (e.g., a robotic hand, or a truck) are used. Specifically, such a Critical Section macro starts by locking the resource (e.g., grabbing an object), continues by using the resource (e.g., manipulating the object) and finishes by releasing the resource (e.g., dropping the object). Hence, such a macro bridges states in which the resource is locked and cannot be used. We also introduce versions of Critical Section macros dealing with multiple resources and phased locks. Usefulness of macros is evaluated using a range of state-of-the-art planners, and a large number of benchmarks from the deterministic and learning tracks of recent editions of the International Planning Competition.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Artificial Intelligence Research
ISSN
1076-9757
e-ISSN
1943-5037
Volume of the periodical
74
Issue of the periodical within the volume
June
Country of publishing house
US - UNITED STATES
Number of pages
42
Pages from-to
691-732
UT code for WoS article
000810515600002
EID of the result in the Scopus database
2-s2.0-85140311439