Qualitative Controller Synthesis for Consumption Markov
Decision Processes

D 2020

Qualitative Controller Synthesis for Consumption Markov Decision Processes

BLAHOUDEK, František, Tomáš BRÁZDIL, Petr NOVOTNÝ, Melkior ORNIK, Pranay THANGEDA et. al.

Basic information

Original name

Qualitative Controller Synthesis for Consumption Markov Decision Processes

Authors

BLAHOUDEK, František (203 Czech Republic), Tomáš BRÁZDIL (203 Czech Republic, belonging to the institution), Petr NOVOTNÝ (203 Czech Republic, guarantor, belonging to the institution), Melkior ORNIK (191 Croatia), Pranay THANGEDA (356 India) and Ufuk TOPCU (792 Turkey)

Edition

Cham, Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part {II}, p. 421-447, 27 pp. 2020

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/20:00114617

Organization unit

Faculty of Informatics

ISBN

978-3-030-53290-1

ISSN

DOI

http://dx.doi.org/10.1007/978-3-030-53291-8_22

UT WoS

000695272500022

Keywords in English

decision making; Markov decision processes; controller synthesis; resource constraints

Abstract

V originále

Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. In a CMDP, the controller possesses a certain amount of a critical resource, such as electric power. Each action of the controller can consume some amount of the resource. Resource replenishment is only possible in special reload states, in which the resource level can be reloaded up to the full capacity of the system. The task of the controller is to prevent resource exhaustion, i.e. ensure that the available amount of the resource stays non-negative, while ensuring an additional linear-time property. We study the complexity of strategy synthesis in consumption MDPs with almost-sure Büchi objectives. We show that the problem can be solved in polynomial time. We implement our algorithm and show that it can efficiently solve CMDPs modelling real-world scenarios.

Links

GA19-15134Y, interní kód MU

Name: Verifikace a analýza pravděpodobnostních programů

Investor: Czech Science Foundation

GJ19-15134Y, research and development project

Name: Verifikace a analýza pravděpodobnostních programů

Citovat

BLAHOUDEK, František, Tomáš BRÁZDIL, Petr NOVOTNÝ, Melkior ORNIK, Pranay THANGEDA and Ufuk TOPCU. Qualitative Controller Synthesis for Consumption Markov Decision Processes. In Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part {II}. Cham: Springer, 2020, p. 421-447. ISBN 978-3-030-53290-1. Available from: https://dx.doi.org/10.1007/978-3-030-53291-8_22.

@inproceedings{1718417,
   author = {Blahoudek, František and Brázdil, Tomáš and Novotný, Petr and Ornik, Melkior and Thangeda, Pranay and Topcu, Ufuk},
   address = {Cham},
   booktitle = {Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part {II}},
   doi = {http://dx.doi.org/10.1007/978-3-030-53291-8_22},
   keywords = {decision making; Markov decision processes; controller synthesis; resource constraints},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Cham},
   isbn = {978-3-030-53290-1},
   pages = {421-447},
   publisher = {Springer},
   title = {Qualitative Controller Synthesis for Consumption Markov Decision Processes},
   year = {2020}
}

TY  - JOUR
ID  - 1718417
AU  - Blahoudek, František - Brázdil, Tomáš - Novotný, Petr - Ornik, Melkior - Thangeda, Pranay - Topcu, Ufuk
PY  - 2020
TI  - Qualitative Controller Synthesis for Consumption Markov Decision Processes
PB  - Springer
CY  - Cham
SN  - 9783030532901
KW  - decision making
KW  - Markov decision processes
KW  - controller synthesis
KW  - resource constraints
N2  - Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. In a CMDP, the controller possesses a certain amount of a critical resource, such as electric power. Each action of the controller can consume some amount of the resource. Resource replenishment is only possible in special reload states, in which the resource level can be reloaded up to the full capacity of the system. The task of the controller is to prevent resource exhaustion, i.e. ensure that the available amount of the resource stays non-negative, while ensuring an additional linear-time property. We study the complexity of strategy synthesis in consumption MDPs with almost-sure Büchi objectives. We show that the problem can be solved in polynomial time. We implement our algorithm and show that it can efficiently solve CMDPs modelling real-world scenarios.
ER  -

BLAHOUDEK, František, Tomáš BRÁZDIL, Petr NOVOTNÝ, Melkior ORNIK, Pranay THANGEDA and Ufuk TOPCU. Qualitative Controller Synthesis for Consumption Markov Decision Processes. In \textit{Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part $\{$II$\}$}. Cham: Springer, 2020, p.~421-447. ISBN~978-3-030-53290-1. Available from: https://dx.doi.org/10.1007/978-3-030-53291-8\_{}22.

Detailed Information on Publication Record