Competing for Resources: Estimating Adversary Strategy for Effective Plan Generation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00360160" target="_blank" >RIV/68407700:21230/22:00360160 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/22:00360160
Result on the web
<a href="https://doi.org/10.1609/aaai.v36i9.21205" target="_blank" >https://doi.org/10.1609/aaai.v36i9.21205</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1609/aaai.v36i9.21205" target="_blank" >10.1609/aaai.v36i9.21205</a>
Alternative languages
Result language
angličtina
Original language name
Competing for Resources: Estimating Adversary Strategy for Effective Plan Generation
Original language description
Effective decision making while competing for limited resources in adversarial environments is important for many real-world applications (e.g. two Taxi companies competing for customers). Decision-making techniques such as Automated planning have to take into account possible actions of adversary (or competing) agents. That said, the agent should know what the competitor will likely do and then generate its plan accordingly. In this paper we propose a novel approach for estimating strategies of the adversary (or the competitor), sampling its actions that might hinder agent's goals by interfering with the agent's actions. The estimated competitor strategies are used in plan generation such that agent's actions have to be applied prior to the ones of the competitor, whose estimated times dictate the deadlines. We empirically evaluate our approach leveraging sampling of competitor's actions by comparing it to the naive approach optimizing the make-span (not taking the competing agent into account at all) and to Nash Equilibrium (mixed) strategies.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
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
Article name in the collection
Proceedings of the 36th AAAI Conference on Artificial Intelligence
ISBN
978-1-57735-876-3
ISSN
2159-5399
e-ISSN
2374-3468
Number of pages
9
Pages from-to
9707-9715
Publisher name
AAAI Press
Place of publication
Menlo Park
Event location
- virtual
Event date
Feb 22, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000893639102081