Using Classical Planning in Adversarial Problems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10408255" target="_blank" >RIV/00216208:11320/19:10408255 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/19:00339629
Result on the web
<a href="http://dx.doi.org/10.1109/ICTAI.2019.00185" target="_blank" >http://dx.doi.org/10.1109/ICTAI.2019.00185</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICTAI.2019.00185" target="_blank" >10.1109/ICTAI.2019.00185</a>

Result language
angličtina
Original language name
Using Classical Planning in Adversarial Problems
Original language description
Many problems from classical planning are applied in the environment with other, possibly adversarial agents. However, plans found by classical planning algorithms lack the robustness against the actions of other agents - the quality of computed plans can be significantly worse compared to the model. To explicitly reason about other (adversarial) agents, the game-theoretic framework can be used. The scalability of game-theoretic algorithms, however, is limited and often insufficient for real-world problems. In this paper, we combine classical domain-independent planning algorithms and game-theoretic strategy-generation algorithm where plans form strategies in the game. Our contribution is threefold. First, we provide the methodology for using classical planning in this game-theoretic framework. Second, we analyze the trade-off between the quality of the planning algorithm and the robustness of final randomized plans and the computation time. Finally, we analyze different variants of integration of classical planning algorithms into the game-theoretic framework and show that at the cost a minor loss in the robustness of final plans, we can significantly reduce the computation time.
Czech name
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Czech description
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Project
<a href="/en/project/GJ17-17125Y" target="_blank" >GJ17-17125Y: Balancing Deliberative and Reactive Behaviour of Intelligent Agents</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)
ISBN
978-1-72813-798-8
ISSN
2375-0197
e-ISSN
—
Number of pages
6
Pages from-to
1335-1340
Publisher name
IEEE
Place of publication
Portland, OR, USA
Event location
Portland, USA
Event date
Nov 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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