Automated Acquisition of Control Knowledge for Classical Planners
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10407358" target="_blank" >RIV/00216208:11320/20:10407358 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/20:00341714
Result on the web
<a href="https://doi.org/10.5220/0009175209590966" target="_blank" >https://doi.org/10.5220/0009175209590966</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0009175209590966" target="_blank" >10.5220/0009175209590966</a>
Alternative languages
Result language
angličtina
Original language name
Automated Acquisition of Control Knowledge for Classical Planners
Original language description
Attributed transition-based domain control knowledge (ATB-DCK) has been proposed as a simple way to express expected (desirable) sequences of actions in a plan with constraints going beyond physics of the en- vironment. This knowledge can be compiled to Planning Domain Description Language (PDDL) to enhance an existing planning domain model and hence any classical planner can exploit it. In the paper, we propose a method to automatically acquire this control knowledge from example plans. First, a regular expression rep- resenting provided plans is found. Then, this expression is extended with attributes expressing extra relations among the actions and hence going beyond regular languages. The final expression is then translated, through ATB-DCK, to PDDL to enhance a planning domain model. We will empirically demonstrate that such an enhanced domain model improves efficiency of existing state-of-the-art planning engines.
Czech name
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Czech description
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Classification
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)
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
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) - Volume 2
ISBN
978-989-758-395-7
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
959-966
Publisher name
SCITEPRESS – Science and Technology Publications, Lda.
Place of publication
SETUBAL
Event location
Valletta, Malta
Event date
Feb 22, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000570769000109