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• Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model AI翻译
  作者：Li, Gen; Wei, Yuting; Chi, Yuejie; Chen, Yuxin
  作者单位：University of Pennsylvania; Carnegie Mellon University; University of Pennsylvania
  摘要：This paper is concerned with the sample efficiency of reinforcement learning, assuming access to a generative model (or simulator). We first consider gamma-discounted infinite-horizon Markov decision processes (MDPs) with state space S and action space A. Despite a number of prior works tackling this problem, a complete picture of the trade-offs between sample complexity and statistical accuracy has yet to be determined. In particular, all prior results suffer from a severe sample size barrier...
• Identifying Merger Opportunities: The Case of Air Traffic Control AI翻译
  作者：Adler, Nicole; Olesen, Ole Bent; Volta, Nicola
  作者单位：Hebrew University of Jerusalem; University of Southern Denmark; Cranfield University
  摘要：Horizontal mergers and acquisitions offer firms the means to grow. However, forecasting these actions' potential effects on the market is not a simple task. We propose a model that identifies optimal horizontal merger configurations for an industry. The model endogenizes the merger choice by maximizing the overall potential efficiency gain at the level of an industry or firm with multiple branches. We further extend the model to consider mergers that create contiguous firms, should network eff...
• Persuading Risk-Conscious Agents: A Geometric Approach AI翻译
  作者：Anunrojwong, Jerry; Iyer, Krishnamurthy; Lingenbrink, David
  作者单位：Columbia University; University of Minnesota System; University of Minnesota Twin Cities; Cornell University
  摘要：We consider a persuasion problem between a sender and a receiver where utility may be nonlinear in the latter's belief; we call such receivers risk conscious. Such utility models arise when the receiver exhibits systematic biases away from expected utility maximization, such as uncertainty aversion (e.g., from sensitivity to the variance of the waiting time for a service). Because of this nonlinearity, the standard approach to finding the optimal persuasion mechanism using revelation principle...
• Provably Good Region Partitioning for On-Time Last-Mile AI翻译
  作者：Carlsson, John Gunnar; Liu, Sheng; Salari, Nooshin; Yu, Han
  作者单位：University of Southern California; University of Toronto; University of Alberta; McMaster University
  摘要：On-time last-mile delivery is expanding rapidly as people expect faster delivery of goods ranging from grocery to medicines. Managing on-time delivery systems is challenging because of the underlying uncertainties and combinatorial nature of the routing decision. In practice, the efficiency of such systems also hinges on the driver's familiarity with the local neighborhood. This paper studies the optimal region partitioning policy to minimize the expected delivery time of customer orders in a ...
• A Sequential Model for High-Volume Recruitment Under Random Yields AI翻译
  作者：Du, Lilun; Li, Qing; Yu, Peiwen
  作者单位：City University of Hong Kong; Hong Kong University of Science & Technology; Chongqing University
  摘要：We model a multiphase and high-volume recruitment process as a large-scale dynamic program. The success of the process is measured by a reward, which is the total assessment score of accepted candidates minus the penalty cost of the number of accepted candidates in the end deviating from a preset hiring target. For a recruiter, two questions are important: How many offers should be made in each phase? And how does the number of phases affect the reward? We consider an upper bound, which is obt...
• Mechanism Design Under Approximate Incentive Compatibility AI翻译
  作者：Balseiro, Santiago R.; Besbes, Omar; Castro, Francisco
  作者单位：Columbia University; University of California System; University of California Los Angeles
  摘要：A fundamental assumption in classical mechanism design is that buyers are perfect optimizers. However, in practice, buyers may be limited by their computational capabilities or a lack of information and may not be able to perfectly optimize their response to a mechanism. This has motivated the introduction of approximate incentive compatibility (IC) as an appealing solution concept for practical mechanism design. Although most of the literature has focused on the analysis of particular approxi...
• Incomplete Information VCG Contracts for Common Agency AI翻译
  作者：Alon, Tal; Talgam-Cohen, Inbal; Lavi, Ron; Shamash, Elisheva
  作者单位：Technion Israel Institute of Technology; University of Bath; Keele University
  摘要：We study contract design for welfare maximization in the well-known common agency model introduced in 1986 by Bernheim and Whinston. This model combines the challenges of coordinating multiple principals with the fundamental challenge of contract design: that principals have incomplete information of the agent's choice of action. Our goal is to design contracts that satisfy truthfulness of the principals, welfare maximization by the agent, and two fundamental properties of individual rationali...
• Resource-Aware Cost-Sharing Methods for Scheduling Games AI翻译
  作者：Christodoulou, George; Gkatzelis, Vasilis; Sgouritsa, Alkmini
  作者单位：Aristotle University of Thessaloniki; Drexel University; Athens University of Economics & Business
  摘要：We study the performance of cost-sharing methods in a selfish scheduling setting where a group of users schedule their jobs on machines with load-dependent cost functions, aiming to minimize their own cost. Anticipating this user behavior, the system designer chooses a decentralized protocol that defines how the cost generated on each machine is to be shared among its users, and the performance of the protocol is evaluated over the Nash equilibria of the induced game. Previous work on selfish ...
• Sequential Competitive Facility Location: Exact and Approximate Algorithms AI翻译
  作者：Qi, Mingyao; Jiang, Ruiwei; Shen, Siqian
  作者单位：Tsinghua University; University of Michigan System; University of Michigan
  摘要：We study a competitive facility location problem (CFLP), where two firms sequentially open new facilities within their budgets, in order to maximize their market shares of demand that follows a probabilistic choice model. This process is a Stackelberg game and admits a bilevel mixed-integer nonlinear program (MINLP) formulation. We derive an equivalent, single-level MINLP reformulation and exploit the problem structures to derive two valid inequalities based on submodularity and concave overes...
• Dynamic Interday and Intraday Scheduling AI翻译
  作者：Zacharias, Christos; Liu, Nan; Begen, Mehmet A.
  作者单位：University of Miami; Boston College; Western University (University of Western Ontario)
  摘要：The simultaneous consideration of appointment day (interday scheduling) and time of day (intraday scheduling) in dynamic scheduling decisions is a theoretical and practical problem that has remained open. We introduce a novel dynamic programming framework that incorporates jointly these scheduling decisions in two timescales. Our model is designed with the intention of bridging the two streams of literature on interday and intraday scheduling and to leverage their latest theoretical developmen...