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In POMDPs, information about the hidden state, delivered through observations, is both valuable to the agent, allowing it to base its actions on better informed internal states, and a "curse", exploding the size and diversity of the…

Machine Learning · Computer Science 2015-12-31 Roy Fox , Naftali Tishby

We study the problem of optimally managing an inventory with unknown demand trend. Our formulation leads to a stochastic control problem under partial observation, in which a Brownian motion with non-observable drift can be singularly…

Optimization and Control · Mathematics 2022-11-28 Salvatore Federico , Giorgio Ferrari , Neofytos Rodosthenous

We present a novel model for capturing the behavior of an agent exhibiting sunk-cost bias in a stochastic environment. Agents exhibiting sunk-cost bias take into account the effort they have already spent on an endeavor when they evaluate…

Computer Science and Game Theory · Computer Science 2021-06-22 Jon Kleinberg , Sigal Oren , Manish Raghavan , Nadav Sklar

In the classical quickest detection problem, one must detect as quickly as possible when a Brownian motion without drift "changes" into a Brownian motion with positive drift. The change occurs at an unknown "disorder" time with exponential…

Probability · Mathematics 2015-05-29 Robert C. Dalang , Albert N. Shiryaev

In this paper, we consider a class of stochastic impulse control problem when there is a fixed delay $\Delta$ between the decision and execution times. The dynamics of the controlled system between two impulses is an arbitrary adapted…

Probability · Mathematics 2026-01-23 Said Hamadène , Ibtissam Hdhiri

In this work we develop a new algorithm for rating of teams (or players) in one-on-one games by exploiting the observed difference of the game-points (such as goals), also known as a margin of victory (MOV). Our objective is to obtain the…

Methodology · Statistics 2022-02-09 Leszek Szczecinski

When learning common skills like driving, beginners usually have domain experts standing by to ensure the safety of the learning process. We formulate such learning scheme under the Expert-in-the-loop Reinforcement Learning where a guardian…

Artificial Intelligence · Computer Science 2021-11-02 Zhenghao Peng , Quanyi Li , Chunxiao Liu , Bolei Zhou

Federated learning (FL) has received significant attention in recent years for its advantages in efficient training of machine learning models across distributed clients without disclosing user-sensitive data. Specifically, in federated…

Machine Learning · Computer Science 2024-10-10 Chung-Hsuan Hu , Zheng Chen , Erik G. Larsson

American options in a multi-asset market model with proportional transaction costs are studied in the case when the holder of an option is able to exercise it gradually at a so-called mixed (randomised) stopping time. The introduction of…

Pricing of Securities · Quantitative Finance 2013-08-14 Alet Roux , Tomasz Zastawniak

It is reported that financial news, especially financial events expressed in news, provide information to investors' long/short decisions and influence the movements of stock markets. Motivated by this, we leverage financial event streams…

Statistical Finance · Quantitative Finance 2020-10-30 Xianchao Wu

Opportunistic Spatial Orthogonalization (OSO) is a cognitive radio scheme that allows the existence of secondary users and hence increases the system throughput, even if the primary user occupies all the frequency bands all the time.…

Information Theory · Computer Science 2009-04-29 Cong Shen , Michael P. Fitz

Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simply put, DOS involves a process of joint channel probing and…

Information Theory · Computer Science 2009-07-14 Chandrashekhar Thejaswi P. S. , Junshan Zhang , Man-On Pun , H. Vincent Poor , Dong Zheng

We study a signaling game between an employer and a potential employee, where the employee has private information regarding their production capacity. At the initial stage, the employee communicates a salary claim, after which the true…

Optimization and Control · Mathematics 2024-06-26 Erik Ekström , Topias Tolonen-Weckström

Information relaxation and duality in Markov decision processes have been studied recently by several researchers with the goal to derive dual bounds on the value function. In this paper we extend this dual formulation to controlled Markov…

Optimization and Control · Mathematics 2014-10-23 Fan Ye , Enlu Zhou

This paper presents an active search trajectory synthesis technique for autonomous mobile robots with nonlinear measurements and dynamics. The presented approach uses the ergodicity of a planned trajectory with respect to an expected…

Robotics · Computer Science 2017-08-31 Lauren M. Miller , Yonatan Silverman , Malcolm A. MacIver , Todd D. Murphey

We consider a collection of statistically identical two-state continuous time Markov chains (channels). A controller continuously selects a channel with the view of maximizing infinite horizon average reward. A switching cost is paid upon…

Information Theory · Computer Science 2021-09-27 Jiesen Wang , Yoni Nazarathy , Thomas Taimre

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

Models of economic decision makers often include idealized assumptions, such as rationality, perfect foresight, and access to all relevant pieces of information. These assumptions often assure the models' internal validity, but, at the same…

General Economics · Economics 2021-07-09 Patrick Reinwald , Stephan Leitner , Friederike Wall

A methodology is developed to identify, as units of study, each decrease in the value of a stock from a given maximum price level. A critical level in the amount of price declines is found to separate a segment operating under a random walk…

Statistical Finance · Quantitative Finance 2017-03-28 Leopoldo Sánchez-Cantú , Carlos Arturo Soto-Campos , Andriy Kryvko

The hidden-action model captures a fundamental problem of principal-agent theory and provides an optimal sharing rule when only the outcome but not the effort can be observed. However, the hidden-action model builds on various explicit and…

General Economics · Economics 2020-04-15 Stephan Leitner , Friederike Wall
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