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People often deviate from expected utility theory when making risky and intertemporal choices. While the effects of probabilistic risk and time delay have been extensively studied in isolation, their interplay and underlying theoretical…

Theoretical Economics · Economics 2025-04-10 Ho Ka Chan , Taro Toyoizumi

We study the tradeoff between fundamental risk and time. A time-constrained agent has to solve a problem. She dynamically allocates effort between implementing a risky initial idea and exploring alternatives. Discovering an alternative…

Theoretical Economics · Economics 2023-02-21 Christoph Carnehl , Johannes Schneider

There is a consensus that human and non-human subjects experience temporal distortions in many stages of their perceptual and decision-making systems. Similarly, intertemporal choice research has shown that decision-makers undervalue future…

Neurons and Cognition · Quantitative Biology 2016-05-31 Pedro A. Ortega , Naftali Tishby

We study online learning for optimal allocation when the resource to be allocated is time. %Examples of possible applications include job scheduling for a computing server, a driver filling a day with rides, a landlord renting an estate,…

Machine Learning · Statistics 2021-11-05 Etienne Boursier , Tristan Garrec , Vianney Perchet , Marco Scarsini

Time-inconsistency is a characteristic of human behavior in which people plan for long-term benefits but take actions that differ from the plan due to conflicts with short-term benefits. Such time-inconsistent behavior is believed to be…

Computer Science and Game Theory · Computer Science 2025-01-15 Yasunori Akagi , Naoki Marumo , Takeshi Kurashima

This paper investigates a novel behavioral feature of recursive preferences: aversion to risks that persist over time, or simply \textit{correlation aversion}. Greater persistence provides information about future consumption but reduces…

Theoretical Economics · Economics 2026-03-24 Lorenzo Maria Stanca

Snapshots of "best" (or "worst") experience are known to dominate human memory and may thus also have a significant effect on future behaviour. We consider here a model of repeated decision-making where, at every time step, an agent takes…

Statistical Mechanics · Physics 2022-02-18 Evangelos Mitsokapas , Rosemary J. Harris

Agents that plan and act in the real world must deal with the fact that time passes as they are planning. When timing is tight, there may be insufficient time to complete the search for a plan before it is time to act. By commencing…

Artificial Intelligence · Computer Science 2023-03-07 Amihay Elboher , Ava Bensoussan , Erez Karpas , Wheeler Ruml , Shahaf S. Shperberg , Solomon E. Shimony

An agent choosing between various actions tends to take the one with the lowest cost. But this choice is arguably too rigid (not adaptive) to be useful in complex situations, e.g., where exploration-exploitation trade-off is relevant in…

Data Analysis, Statistics and Probability · Physics 2018-12-04 Armen E. Allahverdyan , Aram Galstyan , Ali E. Abbas , Zbigniew R. Struzik

Individuals working towards a goal often exhibit time inconsistent behavior, making plans and then failing to follow through. One well-known model of such behavioral anomalies is present-bias discounting: individuals over-weight present…

Computer Science and Game Theory · Computer Science 2016-06-10 Nick Gravin , Nicole Immorlica , Brendan Lucier , Emmanouil Pountourakis

An agent acquires information dynamically until her belief about a binary state reaches an upper or lower threshold. She can choose any signal process subject to a constraint on the rate of entropy reduction. Strategies are ordered by "time…

Theoretical Economics · Economics 2024-08-23 Daniel Chen , Weijie Zhong

Timing decisions are common: when to file your taxes, finish a referee report, or complete a task at work. We ask whether time preferences can be inferred when \textsl{only} task completion is observed. To answer this question, we analyze…

Theoretical Economics · Economics 2019-05-13 Paul Heidhues , Philipp Strack

Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility functions and internal models. When such problems have…

Artificial Intelligence · Computer Science 2025-09-25 Daniel Jarne Ornia , Nicholas Bishop , Joel Dyer , Wei-Chen Lee , Ani Calinescu , Doyne Farmer , Michael Wooldridge

Recent work has considered theoretical models for the behavior of agents with specific behavioral biases: rather than making decisions that optimize a given payoff function, the agent behaves inefficiently because its decisions suffer from…

Computer Science and Game Theory · Computer Science 2017-06-06 Jon Kleinberg , Sigal Oren , Manish Raghavan

Algorithmic predictions are increasingly informing societal resource allocations by identifying individuals for targeting. Policymakers often build these systems with the assumption that by gathering more observations on individuals, they…

Machine Learning · Computer Science 2025-03-04 Ali Shirali , Ariel Procaccia , Rediet Abebe

People are often reluctant to sell a house, or shares of stock, below the price at which they originally bought it. While this is generally not consistent with rational utility maximization, it does reflect two strong empirical regularities…

Computer Science and Game Theory · Computer Science 2021-06-02 Jon Kleinberg , Robert Kleinberg , Sigal Oren

This paper proposes a model of decision-making under uncertainty in which an agent is constrained in her cognitive ability to consider complex acts. We identify the complexity of an act according to the corresponding partition of state…

Theoretical Economics · Economics 2024-06-27 Yuan Gu , Chao Hung Chan

Individuals are often faced with temptations that can lead them astray from long-term goals. We're interested in developing interventions that steer individuals toward making good initial decisions and then maintaining those decisions over…

Machine Learning · Computer Science 2022-03-15 Shruthi Sukumar , Adrian F. Ward , Camden Elliott-Williams , Shabnam Hakimi , Michael C. Mozer

This paper explores the behavior of present-biased agents, that is, agents who erroneously anticipate the costs of future actions compared to their real costs. Specifically, the paper extends the original framework proposed by Akerlof…

Optimization and Control · Mathematics 2021-01-01 Fedor V. Fomin , Pierre Fraigniaud , Petr A. Golovach

Evidence-based decision-making entails collecting (costly) observations about an underlying phenomenon of interest, and subsequently committing to an (informed) decision on the basis of accumulated evidence. In this setting, active sensing…

Machine Learning · Statistics 2020-06-26 Daniel Jarrett , Mihaela van der Schaar
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