We study a sequential resource allocation prob-lem 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. Allocating more resources to a given job in-creases the probability that it completes, but with a cut-off. Specifically, we assume a linear model where the probability increases linearly until it equals one, after which allocating additional re-sources is wasteful. We assume the difficulty of each job is unknown and present the first algo-rithm for this problem and prove upper and lower bounds on its regret. Despite its apparent sim-plicity, the problem has a rich structure: we show that an appropriate opti...
Dans cette thèse, nous étudions des stratégies d’allocation séquentielle de ressources. Le modèle st...
We consider an experimental setting in which a matching of resources to participants has to be chose...
A stochastic combinatorial semi-bandit with a linear payoff is a sequential learning problem where a...
We study a sequential resource allocation prob-lem involving a fixed number of recurring jobs. At ea...
Abstract We study an idealised sequential resource allocation problem. In each time step the learner...
In sequential decision making, an algorithm interacts with an environment, where it can learn from t...
We study a resource allocation problem with varying requests and with resources of limited capacity ...
International audienceWe consider the classical problem of sequential resource allocation where a de...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
Abstract. We consider the problem of minimizing the total cost to run a sequence of n tasks in the g...
155 pagesWe consider multi-action restless bandits with multiple resource constraints, also referred...
This thesis is dedicated to the study of resource allocation problems in uncertain environments, whe...
We present algorithms for a class of resource allocation problems both in the online setting with st...
We consider a class of stochastic sequential allocation problems - restless multi-armed bandits (RMA...
Dans cette thèse, nous étudions des stratégies d’allocation séquentielle de ressources. Le modèle st...
We consider an experimental setting in which a matching of resources to participants has to be chose...
A stochastic combinatorial semi-bandit with a linear payoff is a sequential learning problem where a...
We study a sequential resource allocation prob-lem involving a fixed number of recurring jobs. At ea...
Abstract We study an idealised sequential resource allocation problem. In each time step the learner...
In sequential decision making, an algorithm interacts with an environment, where it can learn from t...
We study a resource allocation problem with varying requests and with resources of limited capacity ...
International audienceWe consider the classical problem of sequential resource allocation where a de...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
In this dissertation, we study several Markovian problems of optimal sequential decisions by focusin...
Abstract. We consider the problem of minimizing the total cost to run a sequence of n tasks in the g...
155 pagesWe consider multi-action restless bandits with multiple resource constraints, also referred...
This thesis is dedicated to the study of resource allocation problems in uncertain environments, whe...
We present algorithms for a class of resource allocation problems both in the online setting with st...
We consider a class of stochastic sequential allocation problems - restless multi-armed bandits (RMA...
Dans cette thèse, nous étudions des stratégies d’allocation séquentielle de ressources. Le modèle st...
We consider an experimental setting in which a matching of resources to participants has to be chose...
A stochastic combinatorial semi-bandit with a linear payoff is a sequential learning problem where a...