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The ontological and epistemic complexities inherent in the moral domain make it challenging to establish clear standards for evaluating the performance of a moral machine. In this paper, we present a formal method to describe Ethical…

Artificial Intelligence · Computer Science 2025-07-15 Abeer Dyoub , Francesca A. Lisi

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf

The paper concerns the probabilistic evaluation of plans in the presence of unmeasured variables, each plan consisting of several concurrent or sequential actions. We establish a graphical criterion for recognizing when the effects of a…

Artificial Intelligence · Computer Science 2013-02-21 Judea Pearl , James M. Robins

Posterior predictive p-values are a common approach to Bayesian model-checking. This article analyses their frequency behaviour, that is, their distribution when the parameters and the data are drawn from the prior and the model…

Statistics Theory · Mathematics 2015-03-31 Patrick Rubin-Delanchy , Daniel John Lawson

There has been a long history of using fuzzy language equivalence to compare the behavior of fuzzy systems, but the comparison at this level is too coarse. Recently, a finer behavioral measure, bisimulation, has been introduced to fuzzy…

Artificial Intelligence · Computer Science 2016-11-15 Yongzhi Cao , Guoqing Chen , Etienne Kerre

Realistic mobility models can demonstrate more precise evaluation results because their parameters are closer to the reality. In this paper a realistic Fuzzy Mobility Model has been proposed. This model has rules which is changeable…

Artificial Intelligence · Computer Science 2011-11-30 Alireza Amirshahi , Mahmood Fathi , Morteza Romoozi , Mohammad Assarian

Causal models bring many benefits to decision-making systems (or agents) by making them interpretable, sample-efficient, and robust to changes in the input distribution. However, spurious correlations can lead to wrong causal models and…

Machine Learning · Computer Science 2020-12-09 Sergei Volodin , Nevan Wichers , Jeremy Nixon

Within the framework proposed in this paper, we address the issue of extending the certain networks to a fuzzy certain networks in order to cope with a vagueness and limitations of existing models for decision under imprecise and uncertain…

Artificial Intelligence · Computer Science 2012-06-06 Abdelkader Heni , Mohamed Nazih Omri , Adel Alimi

The main objective is to present a some variant of the Black - Litterman model. We consider the canonical case when priori return is determined by means such excess return from the CAPM market portfolio which is derived using reverse…

Mathematical Finance · Quantitative Finance 2016-01-05 Krzysztof Echaust , Krzysztof Piasecki

In this paper, we propose a model which simulates odds distributions of pari-mutuel betting system under two hypotheses on the behavior of bettors: 1. The amount of bets increases very rapidly as the deadline for betting comes near. 2. Each…

Econometrics · Economics 2018-05-14 Kurihara Kazutaka , Yohei Tutiya

This paper analyzes identification issues of a behavorial New Keynesian model and estimates it using likelihood-based and limited-information methods with identification-robust confidence sets. The model presents some of the same…

General Economics · Economics 2019-12-18 Joaquim Andrade , Pedro Cordeiro , Guilherme Lambais

We revisit the role of instrumental value as a driver of adaptive behavior. In active inference, instrumental or extrinsic value is quantified by the information-theoretic surprisal of a set of observations measuring the extent to which…

Neurons and Cognition · Quantitative Biology 2020-10-14 Alvaro Ovalle , Simon M. Lucas

Inverse reinforcement learning (IRL) aims to infer an agent's preferences (represented as a reward function $R$) from their behaviour (represented as a policy $\pi$). To do this, we need a behavioural model of how $\pi$ relates to $R$. In…

Machine Learning · Computer Science 2024-03-12 Joar Skalse , Alessandro Abate

This paper proposes a new fuzzy assessing procedure with application in management decision making. The proposed fuzzy approach build the membership functions for system characteristics of a standby repairable system. This method is used to…

Artificial Intelligence · Computer Science 2017-07-07 Shoele Jamali , Mehrdad J. Bani

In this paper the author presents a kind of Soft Computing Technique, mainly an application of fuzzy set theory of Prof. Zadeh [16], on a problem of Medical Experts Systems. The choosen problem is on design of a physician's decision model…

Artificial Intelligence · Computer Science 2010-05-24 Siddharths Sankar Biswas

In this paper we consider a claim that in the natural world there is no fact of the matter about the spatio-temporal separation of events. In order to make sense of such a notion and construct useful models of the world, it is proposed to…

Neurons and Cognition · Quantitative Biology 2024-04-18 Bartosz Jura

In this paper we establish a link between fuzzy and preferential semantics for description logics and Self-Organising Maps, which have been proposed as possible candidates to explain the psychological mechanisms underlying category…

Artificial Intelligence · Computer Science 2022-02-07 Laura Giordano , Valentina Gliozzi , Daniele Theseider Dupré

The practice of stochastic sensitivity analysis described in the decision analysis literature is a testimonial to the need for considering deviations from precise point estimates of uncertainty. We propose the use of Bayesian fuzzy…

Artificial Intelligence · Computer Science 2013-04-10 Pramod Jain , Alice M. Agogino

Procyclicality of historical risk measure estimation means that one tends to over-estimate future risk when present realized volatility is high and vice versa under-estimate future risk when the realized volatility is low. Out of it…

Risk Management · Quantitative Finance 2020-01-03 Marcel Bräutigam , Marie Kratz

In this short paper, we study the simulation of a large system of stochastic processes subject to a common driving noise and fast mean-reverting stochastic volatilities. This model may be used to describe the firm values of a large pool of…

Numerical Analysis · Mathematics 2021-10-13 Andrei Cozma , Christoph Reisinger
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