@article{8789,
abstract = {Cooperation is a ubiquitous and beneficial behavioural trait despite being prone to exploitation by free-riders. Hence, cooperative populations are prone to invasions by selfish individuals. However, a population consisting of only free-riders typically does not survive. Thus, cooperators and free-riders often coexist in some proportion. An evolutionary version of a Snowdrift Game proved its efficiency in analysing this phenomenon. However, what if the system has already reached its stable state but was perturbed due to a change in environmental conditions? Then, individuals may have to re-learn their effective strategies. To address this, we consider behavioural mistakes in strategic choice execution, which we refer to as incompetence. Parametrising the propensity to make such mistakes allows for a mathematical description of learning. We compare strategies based on their relative strategic advantage relying on both fitness and learning factors. When strategies are learned at distinct rates, allowing learning according to a prescribed order is optimal. Interestingly, the strategy with the lowest strategic advantage should be learnt first if we are to optimise fitness over the learning path. Then, the differences between strategies are balanced out in order to minimise the effect of behavioural uncertainty.},
author = {Kleshnina, Maria and Streipert, Sabrina and Filar, Jerzy and Chatterjee, Krishnendu},
issn = {22277390},
journal = {Mathematics},
number = {11},
publisher = {MDPI},
title = {{Prioritised learning in snowdrift-type games}},
doi = {10.3390/math8111945},
volume = {8},
year = {2020},
}
@article{8793,
abstract = {We study optimal election sequences for repeatedly selecting a (very) small group of leaders among a set of participants (players) with publicly known unique ids. In every time slot, every player has to select exactly one player that it considers to be the current leader, oblivious to the selection of the other players, but with the overarching goal of maximizing a given parameterized global (“social”) payoff function in the limit. We consider a quite generic model, where the local payoff achieved by a given player depends, weighted by some arbitrary but fixed real parameter, on the number of different leaders chosen in a round, the number of players that choose the given player as the leader, and whether the chosen leader has changed w.r.t. the previous round or not. The social payoff can be the maximum, average or minimum local payoff of the players. Possible applications include quite diverse examples such as rotating coordinator-based distributed algorithms and long-haul formation flying of social birds. Depending on the weights and the particular social payoff, optimal sequences can be very different, from simple round-robin where all players chose the same leader alternatingly every time slot to very exotic patterns, where a small group of leaders (at most 2) is elected in every time slot. Moreover, we study the question if and when a single player would not benefit w.r.t. its local payoff when deviating from the given optimal sequence, i.e., when our optimal sequences are Nash equilibria in the restricted strategy space of oblivious strategies. As this is the case for many parameterizations of our model, our results reveal that no punishment is needed to make it rational for the players to optimize the social payoff.},
author = {Zeiner, Martin and Schmid, Ulrich and Chatterjee, Krishnendu},
issn = {0166218X},
journal = {Discrete Applied Mathematics},
publisher = {Elsevier},
title = {{Optimal strategies for selecting coordinators}},
doi = {10.1016/j.dam.2020.10.022},
year = {2020},
}
@inproceedings{7955,
abstract = {Simple stochastic games are turn-based 2½-player games with a reachability objective. The basic question asks whether one player can ensure reaching a given target with at least a given probability. A natural extension is games with a conjunction of such conditions as objective. Despite a plethora of recent results on the analysis of systems with multiple objectives, the decidability of this basic problem remains open. In this paper, we present an algorithm approximating the Pareto frontier of the achievable values to a given precision. Moreover, it is an anytime algorithm, meaning it can be stopped at any time returning the current approximation and its error bound.},
author = {Ashok, Pranav and Chatterjee, Krishnendu and Kretinsky, Jan and Weininger, Maximilian and Winkler, Tobias},
booktitle = {Proceedings of the 35th Annual ACM/IEEE Symposium on Logic in Computer Science },
isbn = {9781450371049},
location = {Saarbrücken, Germany},
pages = {102--115},
publisher = {Association for Computing Machinery},
title = {{Approximating values of generalized-reachability stochastic games}},
doi = {10.1145/3373718.3394761},
year = {2020},
}
@article{8788,
abstract = {We consider a real-time setting where an environment releases sequences of firm-deadline tasks, and an online scheduler chooses on-the-fly the ones to execute on a single processor so as to maximize cumulated utility. The competitive ratio is a well-known performance measure for the scheduler: it gives the worst-case ratio, among all possible choices for the environment, of the cumulated utility of the online scheduler versus an offline scheduler that knows these choices in advance. Traditionally, competitive analysis is performed by hand, while automated techniques are rare and only handle static environments with independent tasks. We present a quantitative-verification framework for precedence-aware competitive analysis, where task releases may depend on preceding scheduling choices, i.e., the environment can respond to scheduling decisions dynamically . We consider two general classes of precedences: 1) follower precedences force the release of a dependent task upon the completion of a set of precursor tasks, while and 2) pairing precedences modify the characteristics of a dependent task provided the completion of a set of precursor tasks. Precedences make competitive analysis challenging, as the online and offline schedulers operate on diverging sequences. We make a formal presentation of our framework, and use a GPU-based implementation to analyze ten well-known schedulers on precedence-based application examples taken from the existing literature: 1) a handshake protocol (HP); 2) network packet-switching; 3) query scheduling (QS); and 4) a sporadic-interrupt setting. Our experimental results show that precedences and task parameters can vary drastically the best scheduler. Our framework thus supports application designers in choosing the best scheduler among a given set automatically.},
author = {Pavlogiannis, Andreas and Schaumberger, Nico and Schmid, Ulrich and Chatterjee, Krishnendu},
issn = {19374151},
journal = {IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems},
number = {11},
pages = {3981--3992},
publisher = {IEEE},
title = {{Precedence-aware automated competitive analysis of real-time scheduling}},
doi = {10.1109/TCAD.2020.3012803},
volume = {39},
year = {2020},
}
@inproceedings{7183,
abstract = {A probabilistic vector addition system with states (pVASS) is a finite state Markov process augmented with non-negative integer counters that can be incremented or decremented during each state transition, blocking any behaviour that would cause a counter to decrease below zero. The pVASS can be used as abstractions of probabilistic programs with many decidable properties. The use of pVASS as abstractions requires the presence of nondeterminism in the model. In this paper, we develop techniques for checking fast termination of pVASS with nondeterminism. That is, for every initial configuration of size n, we consider the worst expected number of transitions needed to reach a configuration with some counter negative (the expected termination time). We show that the problem whether the asymptotic expected termination time is linear is decidable in polynomial time for a certain natural class of pVASS with nondeterminism. Furthermore, we show the following dichotomy: if the asymptotic expected termination time is not linear, then it is at least quadratic, i.e., in Ω(n2).},
author = {Brázdil, Tomás and Chatterjee, Krishnendu and Kucera, Antonín and Novotný, Petr and Velan, Dominik},
booktitle = {International Symposium on Automated Technology for Verification and Analysis},
isbn = {9783030317836},
issn = {16113349},
location = {Taipei, Taiwan},
pages = {462--478},
publisher = {Springer Nature},
title = {{Deciding fast termination for probabilistic VASS with nondeterminism}},
doi = {10.1007/978-3-030-31784-3_27},
volume = {11781},
year = {2019},
}