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A problem of optimally allocating partially effective ammunition $x$ to be used on randomly arriving enemies in order to maximize an aircraft's probability of surviving for time~$t$, known as the Bomber Problem, was first posed by…

Probability · Mathematics 2010-07-20 Jay Bartroff , Larry Goldstein , Ester Samuel-Cahn

The Bomber Problem concerns optimal sequential allocation of partially effective ammunition $x$ while under attack from enemies arriving according to a Poisson process over a time interval of length $t$. In the doubly-continuous setting, in…

Probability · Mathematics 2011-03-03 Jay Bartroff

The Fighter problem with discrete ammunition is studied. An aircraft (fighter) equipped with $n$ anti-aircraft missiles is intercepted by enemy airplanes, the appearance of which follows a homogeneous Poisson process with known intensity.…

Probability · Mathematics 2011-07-27 Jay Bartroff , Ester Samuel-Cahn

We study a sequential resource allocation problem involving a fixed number of recurring jobs. At each time-step the manager should distribute available resources among the jobs in order to maximise the expected number of completed jobs.…

Machine Learning · Computer Science 2014-06-17 Tor Lattimore , Koby Crammer , Csaba Szepesvári

This study investigates the problem of $K$-armed linear contextual bandits, an instance of the multi-armed bandit problem, under an adversarial corruption. At each round, a decision-maker observes an independent and identically distributed…

Machine Learning · Computer Science 2023-12-29 Masahiro Kato , Shinji Ito

We consider the airplane refueling problem, where we have a fleet of airplanes that can refuel each other. Each airplane is characterized by specific fuel tank volume and fuel consumption rate, and the goal is to find a drop out order of…

Data Structures and Algorithms · Computer Science 2019-10-09 Jianshu Li , Xiaoyin Hu , Junjie Luo , Jinchuan Cui

We study a sequential resource allocation problem between a fixed number of arms. On each iteration the algorithm distributes a resource among the arms in order to maximize the expected success rate. Allocating more of the resource to a…

Machine Learning · Computer Science 2018-03-29 Yuval Dagan , Koby Crammer

We present a Defense/Attack resource allocation model, where Defender has some number of ``locks" to protect $n$ vulnerable boxes (sites), and Attacker is trying to destroy these boxes, having $m$ ``bombs" that can be placed into the boxes.…

Computer Science and Game Theory · Computer Science 2023-07-06 Isaac M. Sonin

We consider the problem of reward maximization in the dueling bandit setup along with constraints on resource consumption. As in the classic dueling bandits, at each round the learner has to choose a pair of items from a set of $K$ items…

Machine Learning · Computer Science 2023-12-29 Rohan Deb , Aadirupa Saha

This paper studies a sequential decision problem where payoff distributions are known and where the riskiness of payoffs matters. Equivalently, it studies sequential choice from a repeated set of independent lotteries. The decision-maker is…

Theoretical Economics · Economics 2024-01-02 Zengjing Chen , Larry G. Epstein , Guodong Zhang

In this paper, we study the optimal stopping problem in the so-called exploratory framework, in which the agent takes actions randomly conditioning on current state and an entropy-regularized term is added to the reward functional. Such a…

Optimization and Control · Mathematics 2023-09-04 Yuchao Dong

We consider a sequential decision-making problem where an agent can take one action at a time and each action has a stochastic temporal extent, i.e., a new action cannot be taken until the previous one is finished. Upon completion, the…

Machine Learning · Computer Science 2020-03-26 P Sharoff , Nishant A. Mehta , Ravi Ganti

We study a specific \textit{combinatorial pure exploration stochastic bandit problem} where the learner aims at finding the set of arms whose means are above a given threshold, up to a given precision, and \textit{for a fixed time horizon}.…

Machine Learning · Statistics 2016-05-30 Andrea Locatelli , Maurilio Gutzeit , Alexandra Carpentier

We address the problem of allocating limited resources in a network under persistent yet statistically unknown adversarial attacks. Each node in the network may be degraded, but not fully disabled, depending on its available defensive…

Data Structures and Algorithms · Computer Science 2025-07-01 Mansoor Davoodi , Setareh Maghsudi

The airplane refueling problem is a nonlinear combinatorial optimization problem, and its equivalent problem the $n$-vehicle exploration problem is proved to be NP-complete (arXiv:2304.03965v1, The $n$-vehicle exploration problem is…

Computational Complexity · Computer Science 2023-05-23 Jinchuan Cui , Xiaoya Li

We investigate the problem dependent regime in the stochastic Thresholding Bandit problem (TBP) under several shape constraints. In the TBP, the objective of the learner is to output, at the end of a sequential game, the set of arms whose…

Machine Learning · Statistics 2021-06-21 James Cheshire , Pierre Ménard , Alexandra Carpentier

We consider the problem of \textit{best arm identification} with a \textit{fixed budget $T$}, in the $K$-armed stochastic bandit setting, with arms distribution defined on $[0,1]$. We prove that any bandit strategy, for at least one bandit…

Machine Learning · Statistics 2016-05-31 Alexandra Carpentier , Andrea Locatelli

We study a resource allocation problem with varying requests, and with resources of limited capacity shared by multiple requests. It is modeled as a set of heterogeneous Restless Multi-Armed Bandit Problems (RMABPs) connected by constraints…

Optimization and Control · Mathematics 2020-03-30 Jing Fu , Bill Moran , Peter G. Taylor

We study the airplane refueling problem which was introduced by the physicists Gamow and Stern in their classical book Puzzle-Math (1958). Sticking to the original story behind this problem, suppose we have to deliver a bomb in some distant…

Data Structures and Algorithms · Computer Science 2015-12-22 Iftah Gamzu , Danny Segev

We address the problem of identifying the optimal policy with a fixed confidence level in a multi-armed bandit setup, when \emph{the arms are subject to linear constraints}. Unlike the standard best-arm identification problem which is well…

Machine Learning · Computer Science 2024-01-26 Emil Carlsson , Debabrota Basu , Fredrik D. Johansson , Devdatt Dubhashi
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