3,873 research outputs found
The Attack and Defense of Weakest-Link Networks
This paper experimentally examines behavior in a two-player game of attack and defense of a weakest-link network of targets, in which the attacker's objective is to successfully attack at least one target and the defender's objective is diametrically opposed. We apply two benchmark contest success functions (CSFs): the auction CSF and the lottery CSF. Consistent with the theoretical prediction, under the auction CSF, attackers utilize a stochastic “guerilla warfare” strategy — in which a single random target is attacked — more than 80% of the time. Under the lottery CSF, attackers utilize the stochastic guerilla warfare strategy almost 45% of the time, contrary to the theoretical prediction of an equal allocation of forces across the targets.Colonel Blotto, conflict resolution, weakest-link, best-shot, multi-dimensional resource allocation, experiments.
Decentralized Exploration in Multi-Armed Bandits
We consider the decentralized exploration problem: a set of players
collaborate to identify the best arm by asynchronously interacting with the
same stochastic environment. The objective is to insure privacy in the best arm
identification problem between asynchronous, collaborative, and thrifty
players. In the context of a digital service, we advocate that this
decentralized approach allows a good balance between the interests of users and
those of service providers: the providers optimize their services, while
protecting the privacy of the users and saving resources. We define the privacy
level as the amount of information an adversary could infer by intercepting the
messages concerning a single user. We provide a generic algorithm Decentralized
Elimination, which uses any best arm identification algorithm as a subroutine.
We prove that this algorithm insures privacy, with a low communication cost,
and that in comparison to the lower bound of the best arm identification
problem, its sample complexity suffers from a penalty depending on the inverse
of the probability of the most frequent players. Then, thanks to the genericity
of the approach, we extend the proposed algorithm to the non-stationary
bandits. Finally, experiments illustrate and complete the analysis
The Attack and Defense of Weakest-Link Networks
This paper experimentally examines behavior in a two-player game of attack and defense of a weakest-link network of targets, in which the attacker’s objective is to successfully attack at least one target and the defender’s objective is diametrically opposed. We apply two benchmark contest success functions (CSFs): the auction CSF and the lottery CSF. Consistent with the theoretical prediction, under the auction CSF, attackers utilize a stochastic “guerilla warfare” strategy — in which a single random target is attacked — more than 80% of the time. Under the lottery CSF, attackers utilize the stochastic guerilla warfare strategy almost 45% of the time, contrary to the theoretical prediction of an equal allocation of forces across the targets.Colonel Blotto, conflict resolution, weakest-link, best-shot, multi-dimensional resource allocation, experiments
The Attack and Defense of Weakest-Link Networks
This paper experimentally examines behavior in a two-player game of attack and defense of a weakest-link network of targets, in which the attacker’s objective is to successfully attack at least one target and the defender’s objective is diametrically opposed .We apply two benchmark contest success functions (CSFs): the auction CSF and the lottery CSF. Consistent with the theoretical prediction, under the auction CSF, attackers utilize a stochastic “guerilla warfare” strategy - in which a single random target is attacked - more than 80% of the time. Under the lottery CSF, attackers utilize the stochastic guerilla warfare strategy almost 45% of the time, contrary to the theoretical prediction of an equal allocation of forces across the targets.Colonel Blotto, conflict resolution, weakest-link, best-shot, multi-dimensional resource allocation, experiments
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