Failure analysis of a complex system based on partial information about subsystems, with potential applications to aircraft maintenance

In many real-life applications (e.g., in aircraft maintenance), we need to estimate the probability of failure of a complex system (such as an aircraft as a whole or one of its subsystems). Complex systems are usually built with redundancy allowing them to withstand the failure of a small number of components. In this paper, we assume that we know the structure of the system, and, as a result, for each possible set of failed components, we can tell whether this set will lead to a system failure. For each component A, we know the probability P(A) of its failure with some uncertainty: e.g., we know the lower and upper bounds P(A) and P(A) for this probability. Usually, it is assumed that failures of different components are independent events. Our objective is to use all this information to estimate the probability of failure of the entire the complex system. In this paper, we describe several methods for solving this problem, including a new efficient method for such estimation based on Cauchy deviates

A POMDP model for guiding taxi cruising in a congested urban city

10.1007/978-3-642-25324-9_36Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)7094 LNAIPART 1415-42

Incomplete MaxSAT approaches for combinatorial testing

We present a Satisfiability (SAT)-based approach for building Mixed Covering Arrays with Constraints of minimum length, referred to as the Covering Array Number problem. This problem is central in Combinatorial Testing for the detection of system failures. In particular, we show how to apply Maximum Satisfiability (MaxSAT) technology by describing efficient encodings for different classes of complete and incomplete MaxSAT solvers to compute optimal and suboptimal solutions, respectively. Similarly, we show how to solve through MaxSAT technology a closely related problem, the Tuple Number problem, which we extend to incorporate constraints. For this problem, we additionally provide a new MaxSAT-based incomplete algorithm. The extensive experimental evaluation we carry out on the available Mixed Covering Arrays with Constraints benchmarks and the comparison with state-of-the-art tools confirm the good performance of our approaches.We would like to thank specially Akihisa Yamada for the access to several benchmarks for our experiments and for solving some questions about his previous work on Combinatorial Testing with Constraints. This work was partially supported by Grant PID2019-109137GB-C21 funded by MCIN/AEI/10.13039/501100011033, PANDEMIES 2020 by Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR), Departament d’Empresa i Coneixement de la Generalitat de Catalunya; FONDO SUPERA COVID-19 funded by Crue-CSIC-SANTANDER, ISINC (PID2019-111544GB-C21), and the MICNN FPU fellowship (FPU18/02929)

Modeling Alcohol Consumption Using Blog Data

How do the content and writing style of people who drink alcohol beverages stand out from non-drinkers? How much information can we learn about a person's alcohol consumption behavior by reading text that they have authored? This thesis attempts to extend the methods deployed in authorship attribution and authorship profiling research into the domain of automatically identifying the human action of drinking alcohol beverages. I examine how a psycholinguistics dictionary (the Linguistics Inquiry and Word Count lexicon, developed by James Pennebaker), together with Kenneth Burke's concept of words as symbols of human action, and James Wertsch's concept of mediated action provide a framework for analyzing meaningful data patterns from the content of blogs written by consumers of alcohol beverages. The contributions of this thesis to the research field are twofold. First, I show that it is possible to automatically identify blog posts that have content related to the consumption of alcohol beverages. And second, I provide a framework and tools to model human behavior through text analysis of blog data

Executable Attribute Grammars for Modular and Efficient Natural Language Processing

Language-processors that are constructed using top-down recursive-descent with backtracking parsing are highly modular, and are easy to implement and maintain. However, a widely-held inaccurate view is that top-down processors are inherently exponential for ambiguous grammars and cannot accommodate left-recursive syntax rules. It has been known that exponential time and space complexities can be avoided by memoization and compact graph-structured representation, and that left- recursive productions can be accommodated through a variety of techniques. However, until now, memoization, compact representation, and techniques for handling left-recursion have either been presented independently, or else attempts at their integration have compromised modularity and correctness of the resulting parses. Specifying syntax and semantics to describe formal languages using denotational notation of attribute grammars (AGs) has been widely practiced. However, very little work has shown the usefulness of declarative AGs for constructing computational models of natural language. Previous top-down approaches fall short in accommodating ambiguous and general CFGs with arbitrary semantics in one pass as executable specifications. Existing approaches lack in providing a declarative syntax-semantics interface that can take full advantages of dependencies between attributes of syntactic constituents to model linguistically-motivated cases. This thesis solves these shortcomings by proposing a new modular top-down syntactic and semantic analysis system, which is efficient and accommodates all forms of CFGs. Moreover, this system provides notation to declaratively specify semantics by establishing arbitrary dependencies between attributes of syntactic categories to perform linguistically-motivated tasks such as: building directly-executable natural-language query processors, computing meanings of sentences using compositional semantics, performing contextual disambiguation tasks, modelling restrictive classes of languages etc

Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates

Fundamental Features of Metabolic Computing

Hofestädt R. Fundamental Features of Metabolic Computing. In: Batyrshin I, Sidorov G, eds. Advances in Soft Computing: 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Puebla, Mexico, November 26 - December 4, 2011, Proceedings, Part II. Lecture Notes in Computer Science. Vol 7095. Berlin, Heidelberg: Springer; 2011: 143-152.The cell is the basic unit of life and can be interpreted as a chemical machine. The present knowledge of molecular biology allows the characterization of the metabolism as a processing unit/concept. This concept is an evolutionary biochemical product, which has been developed over millions of years. In this paper we will present and discuss the analyzed features of metabolism, which represent the fundamental features of the metabolic computing process. Furthermore, we will compare this molecular computing method with methods which are defined and discussed in computer science. Finally, we will formalize the metabolic processing method