Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.Fundação para a Ciência e a Tecnologia (FCT)-grant SFRH/BD/72795/2010 ; CENTRIA and DI/FCT/UNL for the supplementary fundin

Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations

Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em InformáticaAfter a very brief introduction to the general subject of Knowledge Representation and Reasoning with Logic Programs we analyse the syntactic structure of a logic program and how it can influence the semantics. We outline the important properties of a 2-valued semantics for Normal Logic Programs, proceed to define the new Minimal Hypotheses semantics with those properties and explore how it can be used to benefit some knowledge representation and reasoning mechanisms. The main original contributions of this work, whose connections will be detailed in the sequel, are: • The Layering for generic graphs which we then apply to NLPs yielding the Rule Layering and Atom Layering — a generalization of the stratification notion; • The Full shifting transformation of Disjunctive Logic Programs into (highly nonstratified)NLPs; • The Layer Support — a generalization of the classical notion of support; • The Brave Relevance and Brave Cautious Monotony properties of a 2-valued semantics; • The notions of Relevant Partial Knowledge Answer to a Query and Locally Consistent Relevant Partial Knowledge Answer to a Query; • The Layer-Decomposable Semantics family — the family of semantics that reflect the above mentioned Layerings; • The Approved Models argumentation approach to semantics; • The Minimal Hypotheses 2-valued semantics for NLP — a member of the Layer-Decomposable Semantics family rooted on a minimization of positive hypotheses assumption approach; • The definition and implementation of the Answer Completion mechanism in XSB Prolog — an essential component to ensure XSB’s WAM full compliance with the Well-Founded Semantics; • The definition of the Inspection Points mechanism for Abductive Logic Programs;• An implementation of the Inspection Points workings within the Abdual system [21] We recommend reading the chapters in this thesis in the sequence they appear. However, if the reader is not interested in all the subjects, or is more keen on some topics rather than others, we provide alternative reading paths as shown below. 1-2-3-4-5-6-7-8-9-12 Definition of the Layer-Decomposable Semantics family and the Minimal Hypotheses semantics (1 and 2 are optional) 3-6-7-8-10-11-12 All main contributions – assumes the reader is familiarized with logic programming topics 3-4-5-10-11-12 Focus on abductive reasoning and applications.FCT-MCTES (Fundação para a Ciência e Tecnologia do Ministério da Ciência,Tecnologia e Ensino Superior)- (no. SFRH/BD/28761/2006

Data-driven system identification and model predictive control of a multirotor with an unknown suspended payload

Thesis (MEng)--Stellenbosch University, 2022.ENGLISH ABSTRACT: This thesis considers the problem of stabilised control for a multirotor with an unknown suspended payload. The swinging payload negatively affects the multirotor flight dynamics by inducing oscillations in the system. An adaptive control architecture is proposed to damp these oscillations and produce stable flight with different unknown payloads. The architecture includes a data-driven system identification method that assumes no prior knowledge of the payload dynamics. This method is demonstrated in simulation and with practical flight data. Model Predictive Control (MPC) is applied for swing damping control and is verified with Hardware-in-the-Loop (HITL) simulations. A parameter estimator and Linear Quadratic Regulator (LQR) is used as a baseline control architecture. The LQR uses a predetermined model of the system, which is completed with estimates of the payload mass and cable length. The newly proposed architecture uses Dynamic Mode Decomposition with Control (DMDc) to estimate a linear state-space model and approximate the dynamics without using a predetermined model. The architecture was also tested with a Hankel Alternative View Of Koopman (HAVOK) algorithm which was extended in this work to account for control. An MPC uses the data-driven model to control the multirotor and damp the payload oscillations. A Simulink™ simulator was designed and verified with practical data. Within simulations both the baseline and proposed architectures produced near swing-free control with different payload masses and cable lengths. Even with a dynamic payload producing irregular oscillations, both methods achieved stabilised control. Both architectures also showed effective disturbance rejection. Despite the baseline method using an accurate predetermined model, the proposed method produced equal performances without prior knowledge of the dynamics. The baseline performance degraded significantly with a changed multirotor mass because this parameter was not considered as an unknown. In contrast, the proposed method consistently produced good performances. The accuracy of the DMDc models was verified with practical flight data. The proposed control architecture was also demonstrated in HITL simulations. The hardware executed the MPC at the desired frequency, producing near swing-free control within a Gazebo simulator. Overall, it was shown that the proposed control architecture is practically feasible. Without knowledge of the payload dynamics, a data-driven model can be used with MPC for effective swing damping control with a multirotor.AFRIKAANSE OPSOMMING: Hierdie tesis hanteer die probleem van gestabiliseerde beheer vir ’n multirotor hommeltuig met ’n onbekende hangende loonvrag. Die swaaiende loonvrag be¨ınvloed die vlugdin amika deur ossillasies in die stelsel te veroorsaak. ’n Aanpasbare beheerargitektuur word voorgestel om hierdie ossillasies te demp vir stabiele vlugte met verskillende onbekende loonvragte. Die argitektuur maak gebruik van ’n datagedrewe stelsel-identifikasiemetode wat geen voorafkennis van die loonvragdinamika gebruik nie. Hierdie metode word in simulasies en met praktiese vlugdata gedemonstreer. Model Voorspellende Beheer (MVB) word toegepas vir swaaidempingsbeheer en word geverifieer met Hardeware-in-die-Lus (HIDL) simulasies. ’n Parameter-afskatter en Lineˆere Kwadratiese Gaussiese (LKG) word in die basislyn beheerargitektuur gebruik. Die LKG gebruik ’n voorafbepaalde model van die sisteem wat voltooi word met afskattings van die loonvragmassa en kabellengte. Die nuwe voorgestelde argitektuur gebruik Dinamiese Modus Ontbinding met beheer (DMOb) om ’n lineˆere toestand-ruimte model te bereken en die dinamika af te skat sonder ’n voorafbepaalde model. Die argitektuur is ook getoets met ’n Hankel Alternatiewe Siening van Koopman (HASK)-algoritme wat in hierdie werk uitgebrei is om beheer in te sluit. ’n MVB gebruik die data-gedrewe model om die multirotor te beheer en die loonvrag se ossillasies te demp. ’n Simulink™-simululeerder is ontwerp en geverifieer met praktiese data. In simulasies het beide die basislyn en voorgestelde argitekture byna-swaaivrye beheer met verskillende loon vragmassas en kabellengtes geproduseer. Selfs met ’n dinamiese loonvrag wat onre¨elmatige ossillasies voortbring, het beide metodes gestabiliseerde beheer tot gevolg gehad. Beide ar gitekture het ook effektiewe versteuringsverwerping getoon. Al gebruik die basislynmetode ’n akkurate voorafbepaalde model, het die voorgestelde metode gelyke prestasies gelewer sonder voorafkennis van die dinamika. Die basislyn prestasie het aansienlik afgeneem vir ’n aangepaste multirotormassa omdat hierdie parameter nie as ’n onbekende beskou is nie. Daarteenoor het die voorgestelde metode deurgaans goeie prestasies gelewer. Die akkuraatheid van die DMOb modelle is geverifieer met praktiese vlugdata. Die voorgestelde beheerargitektuur is ook in HIDL-simulasies gedemonstreer. MVB is teen die verlangde frekwensie uitgevoer en het byna-swaaivrye beheer in ’n Gazebo-simululeerder gelewer. In die geheel is dit gewys dat die voorgestelde beheerargitektuur prakties uitvoerbaar is. Sonder kennis van die loonvragdinamika kan ’n data-gedrewe model met MVB gebruik word vir effektiewe swaaidempingsbeheer met ’n multirotor.Master

TweeProfiles4: a weighted multidimensional stream clustering algorithm

O aparecimento das redes sociais abriu aos utilizadores a possibilidade de facilmente partilharem as suas ideias a respeito de diferentes temas, o que constitui uma fonte de informação enriquecedora para diversos campos. As plataformas de microblogging sofreram um grande crescimento e de forma constante nos últimos anos. O Twitter é o site de microblogging mais popular, tornando-se uma fonte de dados interessante para extração de conhecimento. Um dos principais desafios na análise de dados provenientes de redes sociais é o seu fluxo, o que dificulta a aplicação de processos tradicionais de data mining. Neste sentido, a extração de conhecimento sobre fluxos de dados tem recebido um foco significativo recentemente. O TweeProfiles é a uma ferramenta de data mining para análise e visualização de dados do Twitter sobre quatro dimensões: espacial (a localização geográfica do tweet), temporal (a data de publicação do tweet), de conteúdo (o texto do tweet) e social (o grafo dos relacionamentos). Este é um projeto em desenvolvimento que ainda possui muitos aspetos que podem ser melhorados. Uma das recentes melhorias inclui a substituição do algoritmo de clustering original, o qual não suportava o fluxo contínuo dos dados, por um método de streaming. O objetivo desta dissertação passa pela continuação do desenvolvimento do TweeProfiles. Em primeiro lugar, será proposto um novo algoritmo de clustering para fluxos de dados com o objetivo de melhorar o existente. Para esse efeito será desenvolvido um algoritmo incremental com suporte para fluxos de dados multi-dimensionais. Esta abordagem deve permitir ao utilizador alterar dinamicamente a importância relativa de cada dimensão do processo de clustering. Adicionalmente, a avaliação empírica dos resultados será alvo de melhoramento através da identificação e implementação de medidas adequadas de avaliação dos padrões extraídos. O estudo empírico será realizado através de tweets georreferenciados obtidos pelo SocialBus.The emergence of social media made it possible for users to easily share their thoughts on different topics, which constitutes a rich source of information for many fields. Microblogging platforms experienced a large and steady growth over the last few years. Twitter is the most popular microblogging site, making it an interesting source of data for pattern extraction. One of the main challenges of analyzing social media data is its continuous nature, which makes it hard to use traditional data mining. Therefore, mining stream data has also received a lot of attention recently.TweeProfiles is a data mining tool for analyzing and visualizing Twitter data over four dimensions: spatial (the location of the tweet), temporal (the timestamp of the tweet), content (the text of the tweet) and social (relationship graph). This is an ongoing project which still has many aspects that can be improved. For instance, it was recently improved by replacing the original clustering algorithm which could not handle the continuous flow of data with a streaming method. The goal of this dissertation is to continue the development of TweeProfiles. First, the stream clustering process will be improved by proposing a new algorithm. This will be achieved by developing an incremental algorithm with support for multi-dimensional streaming data. Moreover, it should make it possible for the user to dynamically change the relative importance of each dimension in the clustering. Additionally, the empirical evaluation of the results will also be improved.Suitable measures to evaluate the extracted patterns will be identified and implemented. An empirical study will be done using data consisting of georeferenced tweets from SocialBus

Development and evaluation of automatic landing control laws for light wing loading STOL aircraft

Automatic flare and decrab control laws were developed for NASA's experimental Twin Otter. This light wing loading STOL aircraft was equipped with direct lift control (DLC) wing spoilers to enhance flight path control. Automatic landing control laws that made use of the spoilers were developed, evaluated in a simulation and the results compared with these obtained for configurations that did not use DLC. The spoilers produced a significant improvement in performance. A simulation that could be operated faster than real time in order to provide statistical landing data for a large number of landings over a wide spectrum of disturbances in a short time was constructed and used in the evaluation and refinement of control law configurations. A longitudinal control law that had been previously developed and evaluated in flight was also simulated and its performance compared with that of the control laws developed. Runway alignment control laws were also defined, evaluated, and refined to result in a final recommended configuration. Good landing performance, compatible with Category 3 operation into STOL runways, was obtained

Modular Logic Programming: Full Compositionality and Conflict Handling for Practical Reasoning

With the recent development of a new ubiquitous nature of data and the profusity of available knowledge, there is nowadays the need to reason from multiple sources of often incomplete and uncertain knowledge. Our goal was to provide a way to combine declarative knowledge bases – represented as logic programming modules under the answer set semantics – as well as the individual results one already inferred from them, without having to recalculate the results for their composition and without having to explicitly know the original logic programming encodings that produced such results. This posed us many challenges such as how to deal with fundamental problems of modular frameworks for logic programming, namely how to define a general compositional semantics that allows us to compose unrestricted modules. Building upon existing logic programming approaches, we devised a framework capable of composing generic logic programming modules while preserving the crucial property of compositionality, which informally means that the combination of models of individual modules are the models of the union of modules. We are also still able to reason in the presence of knowledge containing incoherencies, which is informally characterised by a logic program that does not have an answer set due to cyclic dependencies of an atom from its default negation. In this thesis we also discuss how the same approach can be extended to deal with probabilistic knowledge in a modular and compositional way. We depart from the Modular Logic Programming approach in Oikarinen & Janhunen (2008); Janhunen et al. (2009) which achieved a restricted form of compositionality of answer set programming modules. We aim at generalising this framework of modular logic programming and start by lifting restrictive conditions that were originally imposed, and use alternative ways of combining these (so called by us) Generalised Modular Logic Programs. We then deal with conflicts arising in generalised modular logic programming and provide modular justifications and debugging for the generalised modular logic programming setting, where justification models answer the question: Why is a given interpretation indeed an Answer Set? and Debugging models answer the question: Why is a given interpretation not an Answer Set? In summary, our research deals with the problematic of formally devising a generic modular logic programming framework, providing: operators for combining arbitrary modular logic programs together with a compositional semantics; We characterise conflicts that occur when composing access control policies, which are generalisable to our context of generalised modular logic programming, and ways of dealing with them syntactically: provided a unification for justification and debugging of logic programs; and semantically: provide a new semantics capable of dealing with incoherences. We also provide an extension of modular logic programming to a probabilistic setting. These goals are already covered with published work. A prototypical tool implementing the unification of justifications and debugging is available for download from http://cptkirk.sourceforge.net

Seismic induced architectural damage to masonry structures at Mercury, Nevada

Selected masonry structures in Mercury, Nevada, were inspected for cracking before and after certain nuclear detonations and during periods of no significant nuclear activity. Detonations gave peak particle velocities whose magnitudes approached those experienced in Mississippi during the Salmon event. Findings include evidence that peak particle velocities of 0. 1 to 0. 3 cm/sec caused more cracking than normal; however, cracks at these low levels of motion are not more severe than those occurring naturally