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Related papers: Discounting and Impatience

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Processes (MDPs) often require frequent decision making, that is, taking an action every microsecond, second, or minute. Infinite horizon discount reward formulation is still relevant for a large portion of these applications, because…

Optimization and Control · Mathematics 2014-12-17 Yin-Lam Chow , Junjie Qin

Delay is the norm in bargaining. I propose a novel source of bargaining delay: absentmindedness. Instead of interpreting absentmindedness as a literal memory friction, I use absentmindedness to represent a broader form of bounded…

Theoretical Economics · Economics 2026-03-10 Cole Wittbrodt

Performance modeling is a key issue in queuing theory and operation research. It is well-known that the length of a queue that awaits service or the time spent by a job in a queue depends not only on the service rate, but also crucially on…

Statistical Mechanics · Physics 2024-04-16 Reshmi Roy , Arup Biswas , Arnab Pal

Is an option especially tempting when it is both immediate and certain? I test the effect of risk on the present-bias factor given quasi-hyperbolic discounting. In my experiment workers allocate about thirty to fifty minutes of real-effort…

General Economics · Economics 2024-08-28 J. Lucas Reddinger

Existing observational approaches for learning human preferences, such as inverse reinforcement learning, usually make strong assumptions about the observability of the human's environment. However, in reality, people make many important…

Machine Learning · Statistics 2021-10-29 Cassidy Laidlaw , Stuart Russell

We study generalizations of online bipartite matching in which each arriving vertex (customer) views a ranked list of offline vertices (products) and matches to (purchases) the first one they deem acceptable. The number of products that the…

Data Structures and Algorithms · Computer Science 2023-06-27 Brian Brubach , Nathaniel Grammel , Will Ma , Aravind Srinivasan

Online advertising platforms use automated auctions to connect advertisers with potential customers, requiring effective bidding strategies to maximize profits. Accurate ad impact estimation requires considering three key factors: delayed…

Machine Learning · Computer Science 2025-10-24 Yuwei Cheng , Zifeng Zhao , Haifeng Xu

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main…

Multiagent Systems · Computer Science 2020-11-06 Kshitij Kulkarni , Sven Neth

In an effort to better understand the different ways in which the discount factor affects the optimization process in reinforcement learning, we designed a set of experiments to study each effect in isolation. Our analysis reveals that the…

Machine Learning · Computer Science 2019-12-24 Harm van Seijen , Mehdi Fatemi , Arash Tavakoli

We consider situations where consumers are aware that a statistical model determines the price of a product based on their observed behavior. Using a novel experiment varying the context similarity between participant data and a product, we…

General Economics · Economics 2024-11-14 Inácio Bó , Li Chen , Rustamdjan Hakimov

Groups make decisions on both the production and the distribution of resources. These decisions typically involve a tension between increasing the total level of group resources (i.e. social efficiency) and distributing these resources…

Physics and Society · Physics 2017-01-17 Valerio Capraro , Brice Corgnet , Antonio M. Espín , Roberto Hernán-González

This work is motivated by our collaboration with a large consumer packaged goods (CPG) company. We have found that while the company appreciates the advantages of dynamic pricing, they deem it operationally much easier to plan out a static…

Data Structures and Algorithms · Computer Science 2020-11-24 Will Ma , David Simchi-Levi , Jinglong Zhao

In the modern knowledge economy, success demands sustained focus and high cognitive performance. Research suggests that human cognition is linked to a finite resource, and upon its depletion, cognitive functions such as self-control and…

Computers and Society · Computer Science 2018-09-11 Nathan O. Hodas , Jacob Hunter , Stephen J. Young , Kristina Lerman

I model a rational agent who experiences endogenous deadline pressure in the face of a fixed future deadline. The agent holds a resource stock, and opportunities to spend resources arise randomly according to a Poisson process. When the…

Theoretical Economics · Economics 2025-09-10 Conrad Kosowsky

A prominent theme in behavioural contract theory is the study of present-biased agents represented through quasi-hyperbolic discounting. In a model of competitive credit provision, we study an alternative to this framework in which the…

Theoretical Economics · Economics 2026-02-11 Siddharth Chatterjee , Daniel F. Garrett

Recent advancements in the field of large language models, particularly through the Chain of Thought (CoT) approach, have demonstrated significant improvements in solving complex problems. However, existing models either tend to sacrifice…

Computation and Language · Computer Science 2025-12-30 Yijiong Yu

A dynamic model of collective consumption and saving decisions made by a finite number of agents with constant but different discount rates is developed. Collective utility is a weighted sum of individual utilities with time-varying utility…

Optimization and Control · Mathematics 2018-07-18 Luis A. Alcala

We study the possibility of achieving the Carnot efficiency in a finite-power underdamped Brownian Carnot cycle. Recently, it was reported that the Carnot efficiency is achievable in a general class of finite-power Carnot cycles in the…

Statistical Mechanics · Physics 2021-04-19 Kosuke Miura , Yuki Izumida , Koji Okuda

Citation recommendation is an important task to assist scholars in finding candidate literature to cite. Traditional studies focus on static models of recommending citations, which do not explicitly distinguish differences between papers…

Information Retrieval · Computer Science 2021-01-20 Shutian Ma , Heng Zhang , Chengzhi Zhang , Xiaozhong Liu

Recommender systems are a ubiquitous feature of online platforms. Increasingly, they are explicitly tasked with increasing users' long-term satisfaction. In this context, we study a content exploration task, which we formalize as a…

Machine Learning · Computer Science 2023-07-21 Thomas M. McDonald , Lucas Maystre , Mounia Lalmas , Daniel Russo , Kamil Ciosek