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Computer systems can be found everywhere: in space, in our homes, in our cars, in our pockets, and sometimes even in our own bodies. For concerns of safety, economy, and convenience, it is important that such systems work correctly.…

Logic in Computer Science · Computer Science 2019-05-22 Mathias Ruggaard Pedersen

We examine implemented systems for ethical machine reasoning with a view to identifying the practical challenges (as opposed to philosophical challenges) posed by the area. We identify a need for complex ethical machine reasoning not only…

Artificial Intelligence · Computer Science 2018-01-08 Louise Dennis , Michael Fisher

We consider social welfare functions when the preferences of individual agents and society maximize subjective expected utility in the tradition of Savage. A system of axioms is introduced whose unique solution is the social welfare…

Theoretical Economics · Economics 2021-08-12 Florian Brandl

Explainable AI is an emerging field providing solutions for acquiring insights into automated systems' rationale. It has been put on the AI map by suggesting ways to tackle key ethical and societal issues. Existing explanation techniques…

Machine Learning · Computer Science 2022-05-02 Ioannis Mollas , Nick Bassiliades , Grigorios Tsoumakas

The modeling of complex systems such as ecological or socio-economic systems can be very challenging. Although various modeling approaches exist, they are generally not compatible and mutually consistent, and empirical data often do not…

Physics and Society · Physics 2010-07-19 Dirk Helbing

We argue for a foundational epistemic claim and a hypothesis about the production and uses of mathematical epidemiological models, exploring the consequences for our political and socio-economic lives. First, in order to make the best use…

Computers and Society · Computer Science 2021-04-02 Matthias Kaiser , Tatjana Buklijas , Peter Gluckman

Value learning is a crucial aspect of safe and ethical AI. This is primarily pursued by methods inferring human values from behaviour. However, humans care about much more than we are able to demonstrate through our actions. Consequently,…

Artificial Intelligence · Computer Science 2025-05-28 Paul de Font-Reaulx

Physics is based on probabilities as fundamental entities of a mathematical description. Expectation values of observables are computed according to the classical statistical rule. The overall probability distribution for one world covers…

Quantum Physics · Physics 2024-10-28 C. Wetterich

Models of areas of physics in terms of cellular automata have become increasingly popular. Cellular automata (CAs) support the modeling of systems with discrete state component values and enforce the comprehensive specification of the…

Quantum Physics · Physics 2015-08-25 Hans H. Diel

We develop a theory of quantum rational decision making in the tradition of Anscombe and Aumann's axiomatisation of preferences on horse lotteries. It is essentially the Bayesian decision theory generalised to the space of Hermitian…

Quantum Physics · Physics 2016-12-08 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

There are many examples of human decision making which cannot be modeled by classical probabilistic and logic models, on which the current AI systems are based. Hence the need for a modeling framework which can enable intelligent systems to…

Artificial Intelligence · Computer Science 2018-08-15 Sagar Uprety , Dawei Song

Agents act to bring about a state of the world that is more compatible with their personal or institutional values. To formalise this intuition, the paper proposes an action framework based on the STRIPS formalisation. Technically, the…

Multiagent Systems · Computer Science 2024-03-26 Adam Wyner , Tomasz Zurek , DOrota Stachura-Zurek

Harsanyi (1955) showed that the only way to aggregate individual preferences into a social preference which satisfies certain desirable properties is ``utilitarianism'', whereby the social utility function is a weighted average of…

Theoretical Economics · Economics 2024-11-05 Federico Echenique , Quitzé Valenzuela-Stookey

Causality is omnipresent in scientists' verbalisations of their understanding, even though we have no formal consensual scientific definition for it. In Automata Networks, it suffices to say that automata "influence" one another to…

Other Computer Science · Computer Science 2016-10-28 Mathilde Noual

This book-length article combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence (AI). The behavior of future AI systems can be described by mathematical equations, which are adapted…

Artificial Intelligence · Computer Science 2015-11-18 Bill Hibbard

The purpose of this paper is to present an idealized hypotheses-drawn model describing dynamics of variability in business and other social areas. A new construct is introduced called the Bayesian space of assessments to consider changes in…

Optimization and Control · Mathematics 2024-06-13 Michael Zhdanov

This paper develops a rigorous mathematical framework for egalitarian ethics by integrating formal tools from economics and mathematics. We motivate the formalism by investigating the limitations of conventional informal approaches by…

General Economics · Economics 2026-04-14 Shuang Wei

A basic model is provided that places active, intentional choices by biological organisms on a solid physical footing. The model is provisionally called "Agent Choice via Quantum Flux." It brings to bear specific physics on living systems…

Quantum Physics · Physics 2026-04-09 R. E. Kastner

Although artificial intelligence (AI) is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a responsible way. Many AI ethics principles and guidelines for…

Artificial Intelligence · Computer Science 2022-07-22 Qinghua Lu , Liming Zhu , Xiwei Xu , Jon Whittle , David Douglas , Conrad Sanderson

We consider two active binary-classification problems with atypical objectives. In the first, active search, our goal is to actively uncover as many members of a given class as possible. In the second, active surveying, our goal is to…

Machine Learning · Computer Science 2016-11-11 Roman Garnett , Yamuna Krishnamurthy , Xuehan Xiong , Jeff Schneider , Richard Mann
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