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作者：Krishnasamy, Subhashini; Sen, Rajat; Johari, Ramesh; Shakkottai, Sanjay
作者单位：University of Texas System; University of Texas Austin; Stanford University
摘要：Consider a queueing system consisting of multiple servers. Jobs arrive over time and enter a queue for service; the goal is to minimize the size of this queue. At each opportunity for service, at most one server can be chosen, and at most one job can be served. Service is successful with a probability (the service probability) that is a priori unknown for each server. An algorithm that knows the service probabilities (the genie) can always choose the server of highest service probability. We s...
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作者：Zhou, Zhengyuan; Mertikopoulos, Panayotis; Moustakas, Aris L.; Bambos, Nicholas; Glynn, Peter
作者单位：New York University; Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS); CNRS - Institute of Physics (INP); Inria; National & Kapodistrian University of Athens; Stanford University
摘要：We consider the target-rate power management problem for wireless networks; and we propose two simple, distributed power management schemes that regulate power in a provably robust manner by efficiently leveraging past information. Both schemes are obtained via a combined approach of learning and game design where we (1) design a game with suitable payoff functions such that the optimal joint power profile in the original power management problem is the unique Nash equilibrium of the designed ...
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作者：Zheng, Zemin; Lv, Jinchi; Lin, Wei
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Southern California; Peking University; Peking University
摘要：As a popular tool for producing meaningful and interpretable models, large-scale sparse learning works efficiently in many optimization applications when the underlying structures are indeed or close to sparse. However, naively applying the existing regularization methods can result in misleading outcomes because of model mis-specification. In this paper, we consider nonsparse learning under the factors plus sparsity structure, which yields a joint modeling of sparse individual effects and com...
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作者：Wu, Manxi; Amin, Saurabh; Ozdaglar, Asuman E.
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
摘要：We study a routing game in an environment with multiple heterogeneous information systems and an uncertain state that affects edge costs of a congested network. Each information system sends a noisy signal about the state to its subscribed traveler population. Travelers make route choices based on their private beliefs about the state and other populations' signals. The question then arises, How does the presence of asymmetric and incomplete information affect the travelers' equilibrium route ...
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作者：Cao, Ping; He, Shuangchi; Huang, Junfei; Liu, Yunan
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; National University of Singapore; Chinese University of Hong Kong; North Carolina State University
摘要：There are two basic queue structures commonly adopted in service systems: the pooled structure, where waiting customers are organized into a single queue served by a group of servers, and the dedicated structure, where each server has her own queue. Although the pooled structure, known to minimize the servers' idle time, is widely used in large-scale service systems, this study reveals that the dedicated structure, along with the join-the-shortest-queue routing policy, could be more advantageo...
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作者：Russo, Daniel
作者单位：Columbia University
摘要：This paper considers the optimal adaptive allocation of measurement effort for identifying the best among a finite set of options or designs. An experimenter sequentially chooses designs to measure and observes noisy signals of their quality with the goal of confidently identifying the best design after a small number of measurements. This paper proposes three simple and intuitive Bayesian algorithms for adaptively allocating measurement effort and formalizes a sense in which these seemingly n...
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作者：Wang, Jinting; Wang, Zhongbin; Liu, Yunan
作者单位：Central University of Finance & Economics; Nankai University; Beijing Jiaotong University; North Carolina State University
摘要：In this article, we introduce a service grade differentiation policy for queueing models with customer retrials. We show that the average waiting time can be reduced through strategically allocating the rates of service and retrial times without needing additional service capacity. Countering to the intuition that higher service variability usually yields a larger delay, we show that the benefits of our simultaneous service-and-retrial differentiation policy outweigh the impact of the increase...
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作者：Yang, Jiankui; Yao, David D.; Ye, Heng-Qing
作者单位：Beijing University of Posts & Telecommunications; Columbia University; Hong Kong Polytechnic University
摘要：The goal of this paper is to illustrate the optimality of reflection control in three different settings, to bring out their connections and to contrast their distinctions. First, we study the control of a Brownian motion with a negative drift, so as to minimize a long-run average cost objective. Weprove the optimality of the reflection control, which prevents the Brownian motion from dropping below a certain level by cancelling out from time to time part of the negative drift; and we show tha...
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作者：Jiang, Daniel R.; Al-Kanj, Lina; Powell, Warren B.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Princeton University
摘要：Monte Carlo tree search (MCTS), most famously used in game-play artificial intelligence (e.g., the game of Go), is a well-known strategy for constructing approximate solutions to sequential decision problems. Its primary innovation is the use of a heuristic, known as a default policy, to obtain Monte Carlo estimates of downstream values for states in a decision tree. This information is used to iteratively expand the tree toward regions of states and actions that an optimal policy might visit....
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作者：Xu, Kuang; Zhong, Yuan
作者单位：Stanford University; University of Chicago
摘要：We propose a general framework, dubbed stochastic processing under imperfect information, to study the impact of information constraints and memories on dynamic resource allocation. The framework involves a stochastic processing network (SPN) scheduling problem in which the scheduler may access the system state only through a noisy channel, and resource allocation decisions must be carried out through the interaction between an encoding policy (that observes the state) and allocation policy (t...
