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A model for decision making that generalizes Expected Utility Maximization is presented. This model, Expected Qualitative Utility Maximization, encompasses the Maximin criterion. It relaxes both the Independence and the Continuity…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

Value [4][5] is typically modeled using a continuous representation (i.e., a Real number). A discrete representation of value has recently been postulated [6]. A quantized representation of probability in the brain was also posited and…

Neurons and Cognition · Quantitative Biology 2020-09-17 James Tee , Desmond P. Taylor

Understanding how people actually trade off time for money is perhaps the major question in the field of time discounting. There is indeed a vast body of work devoted to explore the underlying mechanisms of the individual decision making…

General Economics · Economics 2023-09-26 Salvatore Greco , Diego Rago

We provide foundations for decisions in face of unlikely events by extending the standard framework of Savage to include preferences indexed by a family of events. We derive a subjective lexicographic expected utility representation which…

Statistics Theory · Mathematics 2016-05-26 Hugo Cruz-Sanchez

Under non-exponential discounting, we develop a dynamic theory for stopping problems in continuous time. Our framework covers discount functions that induce decreasing impatience. Due to the inherent time inconsistency, we look for…

Optimization and Control · Mathematics 2017-03-13 Yu-Jui Huang , Adrien Nguyen-Huu

The ability to predict the future in a given domain can be acquired by discovering empirically from experience certain temporal patterns that tend to repeat unerringly. Previous works in time series analysis allow one to make quantitative…

Artificial Intelligence · Computer Science 2013-04-12 Kaihu Chen

Linear temporal logic (LTL) offers a simplified way of specifying tasks for policy optimization that may otherwise be difficult to describe with scalar reward functions. However, the standard RL framework can be too myopic to find maximally…

Machine Learning · Computer Science 2023-03-06 Cameron Voloshin , Abhinav Verma , Yisong Yue

I study robust comparative statics for risk-averse subjective expected utility (SEU) maximizers. Starting with a finite menu of actions totally ordered by sensitivity to risk, I identify the transformations of her menu that lead a…

Theoretical Economics · Economics 2025-05-27 Mark Whitmeyer

This paper is about the state estimation of timed probabilistic discrete event systems. The main contribution is to propose general procedures for developing state estimation approaches based on artificial neural networks. It is assumed…

Systems and Control · Electrical Eng. & Systems 2025-05-22 Omar Amri , Carla Seatzu , Alessandro Giua , Dimitri Lefebvre

Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative…

Artificial Intelligence · Computer Science 2009-11-10 Ali E. Abbas

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

Storing knowledge of an agent's environment in the form of a probabilistic generative model has been established as a crucial ingredient in a multitude of cognitive tasks. Perception has been formalised as probabilistic inference over the…

Neurons and Cognition · Quantitative Biology 2018-06-22 David G. Nagy , Balázs Török , Gergő Orbán

We propose an efficient algorithm for estimation of possibility based qualitative expected utility. It is useful for decision making mechanisms where each possible decision is assigned a multi-attribute possibility distribution. The…

Artificial Intelligence · Computer Science 2012-07-09 Jakub Brzostowski , Ryszard Kowalczyk

Theoretically as well as experimentally it is investigated how people represent their knowledge in order to make decisions or to share their knowledge with others. Experiment 1 probes into the ways how people 6ather information about the…

Artificial Intelligence · Computer Science 2013-04-15 Alf C. Zimmer

Subjective probability is based on the intuitive idea that probability quantifies the degree of belief that an event will occur. A probability theory based on this idea represents the most general framework for handling uncertainty. A brief…

Data Analysis, Statistics and Probability · Physics 2009-10-31 G. D'Agostini

People often face trade-offs between costs and benefits occurring at various points in time. The predominant discounting approach is to use the exponential form. Central to this approach is the discount rate, a unique parameter that…

Theoretical Economics · Economics 2024-08-13 Bach Dong-Xuan , Philippe Bich

Rewards typically express desirabilities or preferences over a set of alternatives. Here we propose that rewards can be defined for any probability distribution based on three desiderata, namely that rewards should be real-valued, additive…

Artificial Intelligence · Computer Science 2009-12-31 Pedro A. Ortega , Daniel A. Braun

I address the question of measuring the subjective perception of the passage of time at the individual level in relation to its objective duration using a physicist-type treatment. A simple model is thus built in terms of a very small…

Physics and Society · Physics 2024-01-09 Serge Galam

By analysing the restrictions that ensure the existence of capital market equilibrium, we show that the coefficient of relative risk aversion and the subjective discount factor cannot be high simultaneously as they are supposed to be to…

Computational Finance · Quantitative Finance 2016-06-30 Dominique Pepin

One purpose -- quite a few thinkers would say the main purpose -- of seeking knowledge about the world is to enhance our ability to make good decisions. An item of knowledge that can make no conceivable difference with regard to anything we…

Artificial Intelligence · Computer Science 2013-04-12 Henry E. Kyburg