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Related papers: The geometry of moral decision making

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Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here we employ an axiomatic framework for bounded rational decision-making based on a…

Artificial Intelligence · Computer Science 2011-07-29 Pedro A. Ortega , Daniel A. Braun

We study the geometrical properties of the utility space (the space of expected utilities over a finite set of options), which is commonly used to model the preferences of an agent in a situation of uncertainty. We focus on the case where…

Computer Science and Game Theory · Computer Science 2015-11-05 François Durand , Benoît Kloeckner , Fabien Mathieu , Ludovic Noirie

Classic decision-theory is based on the maximum expected utility (MEU) principle, but crucially ignores the resource costs incurred when determining optimal decisions. Here we propose an axiomatic framework for bounded decision-making that…

Artificial Intelligence · Computer Science 2010-07-09 Pedro A. Ortega , Daniel A. Braun

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

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

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

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

Social choice theory offers a wealth of approaches for selecting a candidate on behalf of voters based on their reported preference rankings over options. When voters have underlying utilities for these options, however, using preference…

Computer Science and Game Theory · Computer Science 2025-10-24 Luise Ge , Gregory Kehne , Yevgeniy Vorobeychik

We introduce a new computational model of moral decision making, drawing on a recent theory of commonsense moral learning via social dynamics. Our model describes moral dilemmas as a utility function that computes trade-offs in values over…

Artificial Intelligence · Computer Science 2018-01-16 Richard Kim , Max Kleiman-Weiner , Andres Abeliuk , Edmond Awad , Sohan Dsouza , Josh Tenenbaum , Iyad Rahwan

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

The question of "Justice" still divides social research and moral philosophy. Several Theories of Justice and conceptual approaches compete here, and distributive justice remains a major societal controversy. From an evolutionary point of…

Theoretical Economics · Economics 2021-06-03 Andreas Siemoneit

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e.…

Machine Learning · Statistics 2016-10-07 Pedro A. Ortega , Alan A. Stocker

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

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

Deontological ethics, specifically understood through Immanuel Kant, provides a moral framework that emphasizes the importance of duties and principles, rather than the consequences of action. Understanding that despite the prominence of…

Artificial Intelligence · Computer Science 2024-02-28 Carlos Mougan , Joshua Brand

We show how rate-distortion theory provides a mechanism for automated theory building by naturally distinguishing between regularity and randomness. We start from the simple principle that model variables should, as much as possible, render…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Susanne Still , James P. Crutchfield

Models of bounded rationality include quantum--like (QL) models, which use Hilbert--space amplitudes to represent context and order effects, and entropy--regularised (ER) models, including rational inattention, which smooth expected utility…

Econometrics · Economics 2026-03-03 Anders Karlström , Christer Persson

The moral foundations theory supports that people, across cultures, tend to consider a small number of dimensions when classifying issues on a moral basis. The data also show that the statistics of weights attributed to each moral dimension…

Physics and Society · Physics 2014-03-25 Renato Vicente , Alex Susemihl , João Pedro Jericó , Nestor Caticha

There is a lack of consensus within the literature as to how `fairness' of algorithmic systems can be measured, and different metrics can often be at odds. In this paper, we approach this task by drawing on the ethical frameworks of…

Computers and Society · Computer Science 2023-02-08 Daniel E. Rigobon

We study the utilitarian distortion of social choice mechanisms under the recently proposed learning-augmented framework where some (possibly unreliable) predicted information about the preferences of the agents is given as input. In…

Computer Science and Game Theory · Computer Science 2025-02-11 Aris Filos-Ratsikas , Georgios Kalantzis , Alexandros A. Voudouris
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