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Bounded rationality, that is, decision-making and planning under resource limitations, is widely regarded as an important open problem in artificial intelligence, reinforcement learning, computational neuroscience and economics. This paper…

Machine Learning · Statistics 2015-12-22 Pedro A. Ortega , Daniel A. Braun , Justin Dyer , Kee-Eung Kim , Naftali Tishby

Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete…

Artificial Intelligence · Computer Science 2013-04-11 Eric J. Horvitz

Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that…

Machine Learning · Computer Science 2020-06-30 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

In this paper the theory of flexibly-bounded rationality which is an extension to the theory of bounded rationality is revisited. Rational decision making involves using information which is almost always imperfect and incomplete together…

Artificial Intelligence · Computer Science 2013-06-11 Tshilidzi Marwala

We implement nonparametric revealed-preference tests of subjective expected utility theory and its generalizations. We find that a majority of subjects' choices are consistent with the maximization of some utility function. They respond to…

General Economics · Economics 2021-05-04 Federico Echenique , Taisuke Imai , Kota Saito

Mutually exclusive decisions have been studied for decades. Many well-known decision theories have been defined to help people either to make rational decisions or to interpret people's behaviors, such as expected utility theory, regret…

Economics · Quantitative Finance 2018-01-09 Pengyu Zhu

Bounded rationality investigates utility-optimizing decision-makers with limited information-processing power. In particular, information theoretic bounded rationality models formalize resource constraints abstractly in terms of relative…

Artificial Intelligence · Computer Science 2018-09-07 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

Human decision-making deviates from the optimal solution, that maximizes cumulative rewards, in many situations. Here we approach this discrepancy from the perspective of bounded rationality and our goal is to provide a justification for…

Machine Learning · Computer Science 2019-05-13 Marcel Binz , Dominik Endres

In this paper the theory of semi-bounded rationality is proposed as an extension of the theory of bounded rationality. In particular, it is proposed that a decision making process involves two components and these are the correlation…

Artificial Intelligence · Computer Science 2013-05-28 Tshilidzi Marwala

The random utility model (RUM, McFadden and Richter, 1990) has been the standard tool to describe the behavior of a population of decision makers. RUM assumes that decision makers behave as if they maximize a rational preference over a…

General Economics · Economics 2022-07-05 Victor H. Aguiar , Maria Jose Boccardi , Nail Kashaev , Jeongbin Kim

The dominant theories of rational choice assume logical omniscience. That is, they assume that when facing a decision problem, an agent can perform all relevant computations and determine the truth value of all relevant logical/mathematical…

Artificial Intelligence · Computer Science 2023-07-12 Caspar Oesterheld , Abram Demski , Vincent Conitzer

Rationality is often related to optimal decision making. Humans are known to be bounded rational agents. However, recent advances in computing, and other scientific and technical fields along with large amount of data have led to a feeling…

Computers and Society · Computer Science 2023-06-21 Dibakar Das

Throughout the cognitive-science literature, there is widespread agreement that decision-making agents operating in the real world do so under limited information-processing capabilities and without access to unbounded cognitive or…

Machine Learning · Computer Science 2022-11-01 Dilip Arumugam , Mark K. Ho , Noah D. Goodman , Benjamin Van Roy

A perfectly rational decision-maker chooses the best action with the highest utility gain from a set of possible actions. The optimality principles that describe such decision processes do not take into account the computational costs of…

Artificial Intelligence · Computer Science 2013-12-25 Jordi Grau-Moya , Daniel A. Braun

The goal of this article is to investigate how human participants allocate their limited time to decisions with different properties. We report the results of two behavioral experiments. In each trial of the experiments, the participant…

Neurons and Cognition · Quantitative Biology 2016-07-20 Arash Khodadadi , Pegah Fakhari , Jerome R. Busemeyer

Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we propose an information-theoretic formalization of bounded rational decision-making…

Statistics Theory · Mathematics 2015-06-04 Pedro A. Ortega , Daniel A. Braun

We study the subtlety of optimal paternalism when a utilitarian planner has the power to design a discrete choice set for a heterogeneous population with bounded rationality. We first consider the planning problem in abstraction. We show…

Econometrics · Economics 2026-01-23 Charles F. Manski , Eytan Sheshinski

Rational decision making in its linguistic description means making logical decisions. In essence, a rational agent optimally processes all relevant information to achieve its goal. Rationality has two elements and these are the use of…

Artificial Intelligence · Computer Science 2019-02-14 Tshilidzi Marwala

When robots share the same workspace with other intelligent agents (e.g., other robots or humans), they must be able to reason about the behaviors of their neighboring agents while accomplishing the designated tasks. In practice,…

Robotics · Computer Science 2022-10-18 Junhong Xu , Durgakant Pushp , Kai Yin , Lantao Liu

This survey reviews recent developments in revealed preference theory. It discusses the testable implications of theories of choice that are germane to specific economic environments. The focus is on expected utility in risky environments;…

Theoretical Economics · Economics 2019-12-04 Federico Echenique
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