License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CONCUR.2017.12
URN: urn:nbn:de:0030-drops-78000
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/7800/
Bertrand, Nathalie ;
Dewaskar, Miheer ;
Genest, Blaise ;
Gimbert, Hugo
Controlling a Population
Abstract
We introduce a new setting where a population of agents, each modelled by a finite-state system, are controlled uniformly: the controller applies the same action to every agent. The framework is largely inspired by the control of a biological system, namely a population of yeasts, where the controller may only change the environment common to all cells. We study a synchronisation problem for such populations: no matter how individual agents react to the actions of the controller, the controller aims at driving all agents synchronously to a target state. The agents are naturally represented by a non-deterministic finite state automaton (NFA), the same for every agent, and the whole system is encoded as a 2-player game. The first player chooses actions, and the second player resolves non-determinism for each agent. The game with m agents is called the m-population game. This gives rise to a parameterized control problem (where control refers to 2 player games), namely the population control problem: can playerone control the m-population game for all m in N whatever playertwo does?
In this paper, we prove that the population control problem is decidable, and it is a EXPTIME-complete problem. As far as we know, this is one of the first results on parameterized control. Our algorithm, not based on cut-off techniques, produces winning strategies which are symbolic, that i they do not need to count precisely how the population is spread between states. We also show that if the is no winning strategy, then there is a population size cutoff such that playerone wins the m-population game if and only if m< \cutoff. Surprisingly, \cutoff can be doubly exponential in the number of states of the NFA, with tight upper and lower bounds.
BibTeX - Entry
@InProceedings{bertrand_et_al:LIPIcs:2017:7800,
author = {Nathalie Bertrand and Miheer Dewaskar and Blaise Genest and Hugo Gimbert},
title = {{Controlling a Population}},
booktitle = {28th International Conference on Concurrency Theory (CONCUR 2017)},
pages = {12:1--12:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-048-4},
ISSN = {1868-8969},
year = {2017},
volume = {85},
editor = {Roland Meyer and Uwe Nestmann},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2017/7800},
URN = {urn:nbn:de:0030-drops-78000},
doi = {10.4230/LIPIcs.CONCUR.2017.12},
annote = {Keywords: Model-checking, control, parametric systems}
}
Keywords: |
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Model-checking, control, parametric systems |
Collection: |
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28th International Conference on Concurrency Theory (CONCUR 2017) |
Issue Date: |
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2017 |
Date of publication: |
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01.09.2017 |