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Decisions concerning proof of facts in criminal law must be rational because of what is at stake, but the decision-making process must also be cognitively feasible because of cognitive limitations, and it must obey the relevant legal-procedural constraints. In this topic three approaches to rational reasoning about evidence in criminal law are compared in light of these demands: arguments, probabilities, and scenarios. This is done in six case studies in which different authors analyze a manslaughter case from different theoretical perspectives, plus four commentaries on these case studies. The aim of this topic is to obtain more insight into how the different approaches can be applied in a legal context. This will advance the discussion on rational reasoning about evidence in law and will contribute more widely to cognitive science on a number of topics, including the value of probabilistic accounts of cognition and the problem of dealing with cognitive biases in reasoning under uncertainty in practical contexts.

Multiple Criteria Decision Analysis (MCDA) is a discipline used by decision makers to evaluate conflicting features when choosing among alternatives. MCDA methods are applied in the field of sustainable manufacturing to weigh the importance of traditional criteria when compared to sustainability indicators. However, a recurring issue in MCDA is the uncertainty in the assessments of alternatives. In this project, a novel framework to deal with uncertainty in MCDA has been developed. It uses scenario planning to get optimistic and pessimistic assessments for the different alternatives. Then, assigning probabilities to the scenarios and applying COPRAS-N, an introduced modification of COPRAS-G, 11 weighted scenarios are calculated. Finally, the relative significance and ranking of each alternative are graphed according to the weighted scenarios so that their evolution and the different situations are represented. With the presented approach, internal and external uncertainties can be dealt with at the same time. The final decision is made by analysing the graphics and results and, if necessary, looking at the concepts of expected scenario and average performance introduced in this project. The framework has been applied to 3 case studies with a focus on sustainability found in the literature. The results show that providing a final ranking of alternatives without considering other likely scenarios may lead to wrong decisions. In fact, in Case study 1, the choice of the best alternative would have changed if the developed framework had been applied. Representing all the scenarios has proved to ensure the final decision and enable to evaluate all the possible outcomes, solving in this way the uncertainty. Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura

Dependability has become a necessity in the industrial world during the twentieth century. Dependability is an activity domain that proposes means to increase the attributes of the system in a reasonable time and with a less cost. In systems engineering, dependability is defined as the property that enables system users to place a justified confidence in the service it delivers to them and it is a measure of a system’s availability, reliability, and its maintainability, and maintenance support performance, and, in some cases, other characteristics such as durability, safety and security. The key concept that our work is based on is the availability. The availability A(t) is the ability of a system to be operational at a specific moment. The cost of some system with high availability is very expensive. The designer must compromise between the availability and the economic costs. Users can reject systems that are unsafe, unreliable or insecure. Therefore, any user (or industry) will ask this questionbefore getting any product: "What is the optimal product in the market?" To answer to this question, we must combine the following two points : - The best availability of the system : the user wants a product that lasts as long as possible. - The best cost of the system : the user wants a product without costing him a fortune. Availability calculation is based primarily on knowledge of failure rates and repairs of system components. Availability analysis helps to calculate the ability of a system to provide a required level of performance depending on the level of degradation. Several methods have been used to calculate the availability of a system, amongst which we find the Universal Generating Function (UGF), Inclusion-Exclusion technique, Markov models, etc. These methods employ different probabilistic techniques to evaluate this criterion, but these proposed approaches remain effective only for very specific cases, for example the cases of binary systems. A binary system is a system where only two cases are possible : perfect functioning and total failure. While the transition to multi-state systems (MSS) drastically restricts the application of most of these methods. In real life, the systems corresponds to MSS. In such scenarios, systems and their components can operate at different performance levels between working and failure states. However, the evaluation of the availability of the MSSs is more difficult than in the binary case, because we have to take into account the different combinations of the component failure modes. Throughout this thesis, we search for a method that helps us to compute and to optimize the availability of MSS.; La sûreté de fonctionnement (SdF) est devenue une nécessité dans le monde industriel au cours du XXe siècle. La SdF est un domaine d’activité qui propose des moyens d’augmenter les attributs du système dans un délai raisonnable et à moindre coût. Dans l’ingénierie des systèmes, la SdF est définie comme la propriété qui permet aux utilisateurs du système de placer une confiance justifiée dans le service qu’il leur fournit et c’est une mesure de la disponibilité, de la fiabilité et de la maintenabilité d’un système, et de la performance du support de maintenance, et, dans certains cas, d’autres caractéristiques telles que la durabilité, la sûreté et la sécurité. Le concept sur lequel notre travail est basé est la textbf disponibilité. La disponibilité A(t) est la capacité d’un système à être opérationnel à un moment précis. Le coût d’un système à haute disponibilité est très cher. Le concepteur doit faire un compromis entre la disponibilité et les coûts économiques. Les utilisateurs peuvent rejeter des systèmes dangereux, peu fiables ou non sécurisés. Par conséquent, tout utilisateur (ou industrie) posera cette question avant avoir un produit : "Quel est le produit optimal sur le marché ?" Pour répondre à cette question, nous devons combiner les deux points suivants : - La meilleure disponibilité du système : l’utilisateur souhaite un produit qui dure longtemps le plus possible. - Le meilleur coût du système : l’utilisateur veut un produit sans lui coûter une fortune. Le calcul de la disponibilité est basé principalement sur la connaissance des taux de défaillance et des réparations des composants du système. L’analyse de disponibilité permet de calculer la capacité d’un système à fournir un niveau de performance requis en fonction du niveau de dégradation. Plusieurs méthodes ont été utilisées pour calculer la disponibilité d’un système, parmi lesquelles on trouve la Fonction de Génératrice Universelle (UGF), la technique d’inclusion-exclusion, les modèles de Markov, etc. Ces méthodes utilisent différentes techniques probabilistes pour évaluer ce critère, mais ces approches proposées ne restent efficaces que pour des cas très spécifiques, par exemple les cas de systèmes binaires. Un système binaire est un système où deux cas sont possibles : fonctionnement parfait et défaillance totale. Alors que les systèmes multi-états (SME) restreint considérablement l’application de la plupart de ces méthodes. Dans la vie réelle, les systèmes correspondent à des SME. Dans de tels scénarios, les systèmes et leurs composants peuvent fonctionner à différents niveaux de performances entre l’état de fonctionnement parfait et l’état de défaillance totale. Cependant, l’évaluation de la disponibilité des SME est plus difficile que dans le cas binaire, car il faut tenir compte des différentes combinaisons des modes de défaillance des composants. Tout au long de cette thèse, nous recherchons une méthode qui nous aide à calculer et à optimiser la disponibilité de SME tenant compte le facteur coût.

Dependability has become a necessity in the industrial world during the twentieth century. Dependability is an activity domain that proposes means to increase the attributes of the system in a reasonable time and with a less cost. In systems engineering, dependability is defined as the property that enables system users to place a justified confidence in the service it delivers to them and it is a measure of a system’s availability, reliability, and its maintainability, and maintenance support performance, and, in some cases, other characteristics such as durability, safety and security. The key concept that our work is based on is the availability. The availability A(t) is the ability of a system to be operational at a specific moment. The cost of some system with high availability is very expensive. The designer must compromise between the availability and the economic costs. Users can reject systems that are unsafe, unreliable or insecure. Therefore, any user (or industry) will ask this questionbefore getting any product: "What is the optimal product in the market?" To answer to this question, we must combine the following two points : - The best availability of the system : the user wants a product that lasts as long as possible. - The best cost of the system : the user wants a product without costing him a fortune. Availability calculation is based primarily on knowledge of failure rates and repairs of system components. Availability analysis helps to calculate the ability of a system to provide a required level of performance depending on the level of degradation. Several methods have been used to calculate the availability of a system, amongst which we find the Universal Generating Function (UGF), Inclusion-Exclusion technique, Markov models, etc. These methods employ different probabilistic techniques to evaluate this criterion, but these proposed approaches remain effective only for very specific cases, for example the cases of binary systems. A binary system is a system where only two cases are possible : perfect functioning and total failure. While the transition to multi-state systems (MSS) drastically restricts the application of most of these methods. In real life, the systems corresponds to MSS. In such scenarios, systems and their components can operate at different performance levels between working and failure states. However, the evaluation of the availability of the MSSs is more difficult than in the binary case, because we have to take into account the different combinations of the component failure modes. Throughout this thesis, we search for a method that helps us to compute and to optimize the availability of MSS., La sûreté de fonctionnement (SdF) est devenue une nécessité dans le monde industriel au cours du XXe siècle. La SdF est un domaine d’activité qui propose des moyens d’augmenter les attributs du système dans un délai raisonnable et à moindre coût. Dans l’ingénierie des systèmes, la SdF est définie comme la propriété qui permet aux utilisateurs du système de placer une confiance justifiée dans le service qu’il leur fournit et c’est une mesure de la disponibilité, de la fiabilité et de la maintenabilité d’un système, et de la performance du support de maintenance, et, dans certains cas, d’autres caractéristiques telles que la durabilité, la sûreté et la sécurité. Le concept sur lequel notre travail est basé est la textbf disponibilité. La disponibilité A(t) est la capacité d’un système à être opérationnel à un moment précis. Le coût d’un système à haute disponibilité est très cher. Le concepteur doit faire un compromis entre la disponibilité et les coûts économiques. Les utilisateurs peuvent rejeter des systèmes dangereux, peu fiables ou non sécurisés. Par conséquent, tout utilisateur (ou industrie) posera cette question avant avoir un produit : "Quel est le produit optimal sur le marché ?" Pour répondre à cette question, nous devons combiner les deux points suivants : - La meilleure disponibilité du système : l’utilisateur souhaite un produit qui dure longtemps le plus possible. - Le meilleur coût du système : l’utilisateur veut un produit sans lui coûter une fortune. Le calcul de la disponibilité est basé principalement sur la connaissance des taux de défaillance et des réparations des composants du système. L’analyse de disponibilité permet de calculer la capacité d’un système à fournir un niveau de performance requis en fonction du niveau de dégradation. Plusieurs méthodes ont été utilisées pour calculer la disponibilité d’un système, parmi lesquelles on trouve la Fonction de Génératrice Universelle (UGF), la technique d’inclusion-exclusion, les modèles de Markov, etc. Ces méthodes utilisent différentes techniques probabilistes pour évaluer ce critère, mais ces approches proposées ne restent efficaces que pour des cas très spécifiques, par exemple les cas de systèmes binaires. Un système binaire est un système où deux cas sont possibles : fonctionnement parfait et défaillance totale. Alors que les systèmes multi-états (SME) restreint considérablement l’application de la plupart de ces méthodes. Dans la vie réelle, les systèmes correspondent à des SME. Dans de tels scénarios, les systèmes et leurs composants peuvent fonctionner à différents niveaux de performances entre l’état de fonctionnement parfait et l’état de défaillance totale. Cependant, l’évaluation de la disponibilité des SME est plus difficile que dans le cas binaire, car il faut tenir compte des différentes combinaisons des modes de défaillance des composants. Tout au long de cette thèse, nous recherchons une méthode qui nous aide à calculer et à optimiser la disponibilité de SME tenant compte le facteur coût.

The management of data uncertainty can lead to intractability, in the case of probabilistic databases, or even undecidability, in the case of open-world reasoning under logical rules. My thesis studies how to mitigate these problems by restricting the structure of uncertain data and rules. My first contribution investigates conditions on probabilistic relational instances that ensure the tractability of query evaluation and lineage computation. I show that these tasks are tractable when we bound the treewidth of instances, for various probabilistic frameworks and provenance representations. Conversely, I show intractability under mild assumptions for any other condition on instances. The second contribution concerns query evaluation on incomplete data under logical rules, and under the finiteness assumption usually made in database theory. I show that this task is decidable for unary inclusion dependencies and functional dependencies. This establishes the first positive result for finite open-world query answering on an arbitrary-arity language featuring both referential constraints and number restrictions.; La gestion des données incertaines peut devenir infaisable, dans le cas des bases de données probabilistes, ou même indécidable, dans le cas du raisonnement en monde ouvert sous des contraintes logiques. Cette thèse étudie comment pallier ces problèmes en limitant la structure des données incertaines et des règles. La première contribution présentée s'intéresse aux conditions qui permettent d'assurer la faisabilité de l'évaluation de requêtes et du calcul de lignage sur les instances relationnelles probabilistes. Nous montrons que ces tâches sont faisables, pour diverses représentations de la provenance et des probabilités, quand la largeur d'arbre des instances est bornée. Réciproquement, sous des hypothèses faibles, nous pouvons montrer leur infaisabilité pour toute autre condition imposée sur les instances. La seconde contribution concerne l'évaluation de requêtes sur des données incomplètes et sous des contraintes logiques, sous l'hypothèse de finitude généralement supposée en théorie des bases de données. Nous montrons la décidabilité de cette tâche pour les dépendances d'inclusion unaires et les dépendances fonctionnelles. Ceci constitue le premier résultat positif, sous l'hypothèse de la finitude, pour la réponse aux requêtes en monde ouvert avec un langage d'arité arbitraire qui propose à la fois des contraintes d'intégrité référentielle et des contraintes de cardinalité.

The management of data uncertainty can lead to intractability, in the case of probabilistic databases, or even undecidability, in the case of open-world reasoning under logical rules. My thesis studies how to mitigate these problems by restricting the structure of uncertain data and rules. My first contribution investigates conditions on probabilistic relational instances that ensure the tractability of query evaluation and lineage computation. I show that these tasks are tractable when we bound the treewidth of instances, for various probabilistic frameworks and provenance representations. Conversely, I show intractability under mild assumptions for any other condition on instances. The second contribution concerns query evaluation on incomplete data under logical rules, and under the finiteness assumption usually made in database theory. I show that this task is decidable for unary inclusion dependencies and functional dependencies. This establishes the first positive result for finite open-world query answering on an arbitrary-arity language featuring both referential constraints and number restrictions., La gestion des données incertaines peut devenir infaisable, dans le cas des bases de données probabilistes, ou même indécidable, dans le cas du raisonnement en monde ouvert sous des contraintes logiques. Cette thèse étudie comment pallier ces problèmes en limitant la structure des données incertaines et des règles. La première contribution présentée s'intéresse aux conditions qui permettent d'assurer la faisabilité de l'évaluation de requêtes et du calcul de lignage sur les instances relationnelles probabilistes. Nous montrons que ces tâches sont faisables, pour diverses représentations de la provenance et des probabilités, quand la largeur d'arbre des instances est bornée. Réciproquement, sous des hypothèses faibles, nous pouvons montrer leur infaisabilité pour toute autre condition imposée sur les instances. La seconde contribution concerne l'évaluation de requêtes sur des données incomplètes et sous des contraintes logiques, sous l'hypothèse de finitude généralement supposée en théorie des bases de données. Nous montrons la décidabilité de cette tâche pour les dépendances d'inclusion unaires et les dépendances fonctionnelles. Ceci constitue le premier résultat positif, sous l'hypothèse de la finitude, pour la réponse aux requêtes en monde ouvert avec un langage d'arité arbitraire qui propose à la fois des contraintes d'intégrité référentielle et des contraintes de cardinalité.

Following Lorenz's seminal work on chaos theory in the 1960s, probabilistic approaches to prediction have come to dominate the science of weather and climate forecasting. This paper gives a perspective on Lorenz's work and how it has influenced the ways in which we seek to represent uncertainty in forecasts on all lead times from hours to decades. It looks at how model uncertainty has been represented in probabilistic prediction systems and considers the challenges posed by a changing climate. Finally, the paper considers how the uncertainty in projections of climate change can be addressed to deliver more reliable and confident assessments that support decision-making on adaptation and mitigation.

In recent years, the psychology of reasoning has been undergoing a paradigm shift, with general Bayesian, probabilistic approaches replacing the older, much more restricted binary logic paradigm. At the same time, dual processing theories have been gaining influence. We argue that these developments should be integrated and moreover that such integration is already underway. The new reasoning paradigm should be grounded in dual processing for its algorithmic level of analysis just as it uses Bayesian theory for its computational level of analysis. Moreover, we propose that, within the new paradigm, these levels of analysis reflect on each other. Bayesianism suggests a specific theoretical understanding of dual processing. Just as importantly, the duality in processing carries over to duality in function; although both types of processes compute degrees of belief, they generate different functions.

We present the uncertain probabilistic ordered weighted averaging (UPOWA) operator. It is an aggregation operator that uses probabilities and OWA operators in the same formulation considering the degree of importance of each concept in the analysis. Moreover, it also uses uncertain information assessed with interval numbers in the aggregation process. The main advantage of this aggregation operator is that it is able to use the attitudinal character of the decision maker and the available probabilistic information in an environment where the information is very imprecise and can be assessed with interval numbers. We study some of its main properties and particular cases such as the uncertain probabilistic aggregation (UPA) and the uncertain OWA (UOWA) operator. We also develop an application of the new approach in a multi-person decision-making problem in political management regarding the selection of monetary policies. Thus, we obtain the multiperson UPOWA (MP-UPOWA) operator. We see that this model gives more complete information of the decision problem because it is able to deal with decision making problems under uncertainty and under risk in the same formulation. Article in English. Tikimybiniai sumavimo operatoriai ir jų taikymas priimant grupinius sprendimus neapibrėžtoje aplinkoje Santrauka.Autoriai pristato tikimybinį svertinio vidurkio operatorių, taikytiną neapibrežtumo sąlygomis. Tai tikimybėmis pagrįstas sumavimo operatorius, kuris kartu su svertinio vidurkio operatoriais gali įvertinti alternatyvų svarbumo laipsnį. Be to, jis gali operuoti neapibrežta informacija, išreikšta skaičiais intervaluose. Pagrindinis šio operatoriaus privalumas yra tas, kad jį galima taikyti uždaviniams, kuriuose informacija yra netiksli. Išnagrinėtos kai kurios minėto operatoriaus savybės. Sukurtas metodas pritaikytas monetarinei politikai parinkti, situacijai, kai sprendimus priima žmoniu grupė. Modelis suteikia išsamesnę informaciją apie problemą, nes gali įvertinti neapibrežtumus ir riziką. Reikšminiai žodžiai: operatorius,tikimybės,neapibrežtumas,skaičių intervalas,grupinis sprendimų priėmimas,politika.

We present the uncertain probabilistic ordered weighted averaging (UPOWA) operator. It is an aggregation operator that uses probabilities and OWA operators in the same formulation considering the degree of importance of each concept in the analysis. Moreover, it also uses uncertain information assessed with interval numbers in the aggregation process. The main advantage of this aggregation operator is that it is able to use the attitudinal character of the decision maker and the available probabilistic information in an environment where the information is very imprecise and can be assessed with interval numbers. We study some of its main properties and particular cases such as the uncertain probabilistic aggregation (UPA) and the uncertain OWA (UOWA) operator. We also develop an application of the new approach in a multi-person decision-making problem in political management regarding the selection of monetary policies. Thus, we obtain the multiperson UPOWA (MP-UPOWA) operator. We see that this model gives more complete information of the decision problem because it is able to deal with decision making problems under uncertainty and under risk in the same formulation. Santrauka Autoriai pristato tikimybinį svertinio vidurkio operatorių, taikytiną neapibrežtumo sąlygomis. Tai tikimybėmis pagrįstas sumavimo operatorius, kuris kartu su svertinio vidurkio operatoriais gali įvertinti alternatyvų svarbumo laipsnį. Be to, jis gali operuoti neapibrežta informacija, išreikšta skaičiais intervaluose. Pagrindinis šio operatoriaus privalumas yra tas, kad jį galima taikyti uždaviniams, kuriuose informacija yra netiksli. Išnagrinėtos kai kurios minėto operatoriaus savybės. Sukurtas metodas pritaikytas monetarinei politikai parinkti, situacijai, kai sprendimus priima žmoniu grupė. Modelis suteikia išsamesnę informaciją apie problemą, nes gali įvertinti neapibrežtumus ir riziką. Reikšminiai žodžiai:operatorius,tikimybės,neapibrežtumas,skaičių intervalas,grupinis sprendimų priėmimas,politika

CIVINS (Civilian Institutions) Thesis document In response to the transition by the United States Nuclear Regulatory Commission (NRC) to a risk-informed, performance-based fire protection rulemaking standard, Fire Probabilistic Risk Assessment (PRA) methods have been improved, particularly in the areas of advanced fire modeling and computational methods. In order to gain a more meaningful insight into the methods currently in practice, it was decided that a scenario incorporating the various elements of uncertainty specific to a fire PRA would be analyzed. Fire induced Main Control Room (MCR) abandonment scenarios are a significant contributor to the total Core Damage Frequency (CDF) estimate of many operating nuclear power plants. This report details the simultaneous application of state-of-the-art model and parameter uncertainty techniques to develop a defensible distribution of the probability of a forced MCR abandonment caused by a fire within a MCR benchboard. This report details the simultaneous application of state-of-the-art model and parameter uncertainty techniques to develop a defensible distribution of the probability of a forced MCR abandonment caused by a fire within a MCR. http://archive.org/details/uncertaintyndsen109454939 Contract number: N62271-97-G-0026. CIVINS Approved for public release; distribution is unlimited.

International audience; Dealing consistently with risk and uncertainty across the IPCC reports is a difficult challenge. Huge practical difficulties arise from the Panel's scale and interdisciplinary context, the complexity of the climate change issue and its political context. The key question of this paper is if the observed differences in the handling of uncertainties by the three IPCC Working Groups can be clarified. To address this question, the paper reviews a few key issues on the foundations of uncertainty analysis, and summarizes the history of the treatment of uncertainty by the IPCC. One of the key findings is that there is reason to agree to disagree: the fundamental differences between the issues covered by the IPCC's three interdisciplinary Working Groups, between the type of information available, and between the dominant paradigms of the practitioners, legitimately lead to different approaches. We argue that properly using the IPCC's Guidance Notes for Lead Authors for addressing uncertainty, adding a pedigree analysis for key findings, and particularly communicating the diverse nature of uncertainty to the users of the assessment would increase the quality of the assessment. This approach would provide information about the nature of the uncertainties in addition to their magnitude and the confidence assessors have in their findings.; Ce texte examine le traitement de l'incertitude dans les rapports du Groupe d'experts Intergouvernemental sur les Changements Climatiques (IPCC). La première partie rappelle les différences fondamentales entre probabilités objectives et subjectives, entre probabilités précises et imprécises, ainsi qu'entre les systèmes causaux et intentionels. La seconde partie met en évidence les divergences entre les trois groupes de travail persistantes au cours de l'histoire de l'IPCC. On montre en particulier que les incertitudes sur la notion de coût et de potentiel de réduction ne sont pas quantifiables en termes de probabilités. En conclusion, le texte recommande de reconnaitre la diversité des approches épistémiques dans les différentes disciplines, et d'adopter une caractérisation multidimensionnelle permettant de jauger la confiance des jugements (approche par pedigree).

This paper estimates a sequence of energy-saving technology choices by Dutch glasshouse firms. The model allows for time-constant, firm-specific effects and serial correlation of errors and it is estimated on panel data over the period 1991¿1995. The unobserved error sequences are simulated in the model in such a way that they are consistent with the observed choices. The results suggest that positive revenue shocks encourage adoption of new technologies. The choices also exhibit firm-specific persistency over time. An increase of the price of energy encourages the adoption of a highly efficient energy-saving technology. The probability of investing in energy-saving technologies also decreases with capital invested in structures (e.g. double glazing of glasshouses) and increases with capital in energy installations.

Because the analysis of risky choice in agriculture and rural resource management is important but difficult, we argue that there is a need for some agreed principles on how to proceed. This paper is intended as a first step to this end. We start with the proposition that the importance of risk aversion has generally been exaggerated relative to the task of finding better ways to deduce relevant and reliable probabilities. Getting better probabilities demands careful thought, drawing on what is known about the pitfalls and on evolving insights into better ways of proceeding. Our aim is to stimulate a debate leading to a clearer consensus about better practice in these matters.