Using Classical Planning in Adversarial Problems

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/68407700:21230/19:00339629

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Using Classical Planning in Adversarial Problems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Using Classical Planning in Adversarial Problems

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50803 - Information science (social aspects)

Projekt

<a href="/cs/project/GJ17-17125Y" target="_blank" >GJ17-17125Y: Balancování deliberativního a reaktivního chování inteligentních agentů</a><br>

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 statě ve sborníku

2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)

ISBN

978-1-72813-798-8

ISSN

2375-0197

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1335-1340

Název nakladatele

IEEE

Místo vydání

Portland, OR, USA

Místo konání akce

Portland, USA

Datum konání akce

4. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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