SOS: Safe, Optimal and Small Strategies for Hybrid Markov
Decision Processes

D 2019

SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes

ASHOK, Pranav; Jan KŘETÍNSKÝ; Kim G. LARSEN; Adrien Le COËNT; Jakob Haahr TAANKVIST et al.

Základní údaje

Originální název

SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes

Autoři

ASHOK, Pranav; Jan KŘETÍNSKÝ; Kim G. LARSEN; Adrien Le COËNT; Jakob Haahr TAANKVIST a Maximilian WEININGER

Vydání

Quantitative Evaluation of Systems, 16th International Conference, QEST 2019, Glasgow, UK, September 10-12, 2019, Proceedings. od s. 147-164, 18 s. 2019

Nakladatel

Springer

Další údaje

Typ výsledku

Stať ve sborníku

Označené pro přenos do RIV

Organizační jednotka

Fakulta informatiky

ISBN

9783030302801

ISSN

DOI

https://doi.org/10.1007/978-3-030-30281-8_9

Změněno: 17. 3. 2025 14:43, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

For hybrid Markov decision processes, Stratego can compute strategies that are safe for a given safety property and (in the limit) optimal for a given cost function. Unfortunately, these strategies cannot be exported easily since they are computed as a very long list. In this paper, we demonstrate methods to learn compact representations of the strategies in the form of decision trees. These decision trees are much smaller, more understandable, and can easily be exported as code that can be loaded into embedded systems. Despite the size compression and actual differences to the original strategy, we provide guarantees on both safety and optimality of the decision-tree strategy. On the top, we show how to obtain yet smaller representations, which are still guaranteed safe, but achieve a desired trade-off between size and optimality.

Citovat

ASHOK, Pranav; Jan KŘETÍNSKÝ; Kim G. LARSEN; Adrien Le COËNT; Jakob Haahr TAANKVIST a Maximilian WEININGER. SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes. In Quantitative Evaluation of Systems, 16th International Conference, QEST 2019, Glasgow, UK, September 10-12, 2019, Proceedings. Springer, 2019, s. 147-164. ISBN 9783030302801. Dostupné z: https://doi.org/10.1007/978-3-030-30281-8_9.

@inproceedings{2484803,
   author = {Ashok, Pranav and Křetínský, Jan and Larsen, Kim G. and Coënt, Adrien Le and Taankvist, Jakob Haahr and Weininger, Maximilian},
   booktitle = {Quantitative Evaluation of Systems, 16th International Conference, QEST 2019, Glasgow, UK, September 10-12, 2019, Proceedings.},
   doi = {https://doi.org/10.1007/978-3-030-30281-8_9},
   isbn = {9783030302801},
   pages = {147-164},
   publisher = {Springer},
   title = {SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes},
   year = {2019}
}

TY  - CONF
ID  - 2484803
AU  - Ashok, Pranav - Křetínský, Jan - Larsen, Kim G. - Coënt, Adrien Le - Taankvist, Jakob Haahr - Weininger, Maximilian
PY  - 2019
TI  - SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes
PB  - Springer
SN  - 9783030302801
N2  - For hybrid Markov decision processes, Stratego can compute strategies that are safe for a given safety property and (in the limit) optimal for a given cost function. Unfortunately, these strategies cannot be exported easily since they are computed as a very long list. In this paper, we demonstrate methods to learn compact representations of the strategies in the form of decision trees. These decision trees are much smaller, more understandable, and can easily be exported as code that can be loaded into embedded systems. Despite the size compression and actual differences to the original strategy, we provide guarantees on both safety and optimality of the decision-tree strategy. On the top, we show how to obtain yet smaller representations, which are still guaranteed safe, but achieve a desired trade-off between size and optimality.
ER  -

ASHOK, Pranav; Jan KŘETÍNSKÝ; Kim G. LARSEN; Adrien Le CO$\backslash$''ENT; Jakob Haahr TAANKVIST a Maximilian WEININGER. SOS: Safe, Optimal and Small Strategies for Hybrid Markov Decision Processes. In \textit{Quantitative Evaluation of Systems, 16th International Conference, QEST 2019, Glasgow, UK, September 10-12, 2019, Proceedings.}. Springer, 2019, s.~147-164. ISBN~9783030302801. Dostupné z: https://doi.org/10.1007/978-3-030-30281-8\_{}9.

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