Programming Robots with an Agent-Oriented BDI-based Control Architecture: Explorations using the JaCa and Webots Platforms

La crescente disponibilità di dispositivi meccanici e -soprattutto - elettronici le cui performance aumentano mentre il loro costo diminuisce, ha permesso al campo della robotica di compiere notevoli progressi. Tali progressi non sono stati fatti unicamente per ciò che riguarda la robotica per uso industriale, nelle catene di montaggio per esempio, ma anche per quella branca della robotica che comprende i robot autonomi domestici. Questi sistemi autonomi stanno diventando, per i suddetti motivi, sempre più pervasivi, ovvero sono immersi nello stesso ambiente nel quale vivono gli essere umani, e interagiscono con questi in maniera proattiva. Essi stanno compiendo quindi lo stesso percorso che hanno attraversato i personal computer all'incirca 30 anni fa, passando dall'essere costosi ed ingombranti mainframe a disposizione unicamente di enti di ricerca ed università, ad essere presenti all'interno di ogni abitazione, per un utilizzo non solo professionale ma anche di assistenza alle attività quotidiane o anche di intrattenimento. Per questi motivi la robotica è un campo dell'Information Technology che interessa sempre più tutti i tipi di programmatori software. Questa tesi analizza per prima cosa gli aspetti salienti della programmazione di controllori per robot autonomi (ovvero senza essere guidati da un utente), quindi, come l'approccio basato su agenti sia appropriato per la programmazione di questi sistemi. In particolare si mostrerà come un approccio ad agenti, utilizzando il linguaggio di programmazione Jason e quindi l'architettura BDI, sia una scelta significativa, dal momento che il modello sottostante a questo tipo di linguaggio è basato sul ragionamento pratico degli esseri umani (Human Practical Reasoning) e quindi è adatto alla implementazione di sistemi che agiscono in maniera autonoma. Dato che le possibilità di utilizzare un vero e proprio sistema autonomo per poter testare i controllori sono ridotte, per motivi pratici, economici e temporali, mostreremo come è facile e performante arrivare in maniera rapida ad un primo prototipo del robot tramite l'utilizzo del simulatore commerciale Webots. Il contributo portato da questa tesi include la possibilità di poter programmare un robot in maniera modulare e rapida per mezzo di poche linee di codice, in modo tale che l'aumento delle funzionalità di questo risulti un collo di bottiglia, come si verifica nella programmazione di questi sistemi tramite i classici linguaggi di programmazione imperativi. L'organizzazione di questa tesi prevede un capitolo di background nel quale vengono riportare le basi della robotica, della sua programmazione e degli strumenti atti allo scopo, un capitolo che riporta le nozioni di programmazione ad agenti, tramite il linguaggio Jason -quindi l'architettura BDI - e perché tale approccio è adatto alla programmazione di sistemi di controllo per la robotica. Successivamente viene presentata quella che è la struttura completa del nostro ambiente di lavoro software che comprende l'ambiente ad agenti e il simulatore, quindi nel successivo capitolo vengono mostrate quelle che sono le esplorazioni effettuate utilizzando Jason e un approccio classico (per mezzo di linguaggi classici), attraverso diversi casi di studio di crescente complessità; dopodiché, verrà effettuata una valutazione tra i due approcci analizzando i problemi e i vantaggi che comportano questi. Infine, la tesi terminerà con un capitolo di conclusioni e di riflessioni sulle possibili estensioni e lavori futuri.

SOUPAC program descriptions : statistically oriented users programming and consulting.

Mode of access: Internet.

SOUPAC program descriptions : statistically oriented users programming and consulting.

"Report no. 370-3."

SOUPAC program descriptions : statistically oriented users programming and consulting.

Mode of access: Internet.

Influence apart from Adoption: How Interaction between Programming and Scientific Practices Shapes Modes of Inquiry in Four Oceanography Teams

Thesis (Ph.D.)--University of Washington, 2016-06

Combining data driven programming with component based software development:with applications in geovisualisation and dynamic data driven application systems

Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

Programming Assignment of Programming 3: an Object-Oriented Version of Conway’s Game of Life

These are the instructions for a programming assignment of the subject Programming 3 taught at University of Alicante in Spain. The objective of the assignment is to build an object-oriented version of Conway's game of life in Java. The assignment is divided into four sub-assignments.

Interoperability Challenges in Internet of Things Systems: a Service-Oriented Computing Approach

Internet of Things systems are pervasive systems evolved from cyber-physical to large-scale systems. Due to the number of technologies involved, software development involves several integration challenges. Among them, the ones preventing proper integration are those related to the system heterogeneity, and thus addressing interoperability issues. From a software engineering perspective, developers mostly experience the lack of interoperability in the two phases of software development: programming and deployment. On the one hand, modern software tends to be distributed in several components, each adopting its most-appropriate technology stack, pushing programmers to code in a protocol- and data-agnostic way. On the other hand, each software component should run in the most appropriate execution environment and, as a result, system architects strive to automate the deployment in distributed infrastructures. This dissertation aims to improve the development process by introducing proper tools to handle certain aspects of the system heterogeneity. Our effort focuses on three of these aspects and, for each one of those, we propose a tool addressing the underlying challenge. The first tool aims to handle heterogeneity at the transport and application protocol level, the second to manage different data formats, while the third to obtain optimal deployment. To realize the tools, we adopted a linguistic approach, i.e.\ we provided specific linguistic abstractions that help developers to increase the expressive power of the programming language they use, writing better solutions in more straightforward ways. To validate the approach, we implemented use cases to show that the tools can be used in practice and that they help to achieve the expected level of interoperability. In conclusion, to move a step towards the realization of an integrated Internet of Things ecosystem, we target programmers and architects and propose them to use the presented tools to ease the software development process.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

CrimsonHex: a learning objects repository for programming exercises

A repository of learning objects is a system that stores electronic resources in a technology-mediated learning process. The need for this kind of repository is growing as more educators become eager to use digital educa- tional contents and more of it becomes available. The sharing and use of these resources relies on the use of content and communication standards as a means to describe and exchange educational resources, commonly known as learning objects. This paper presents the design and implementation of a service-oriented reposi- tory of learning objects called crimsonHex. This repository supports new definitions of learning objects for specialized domains and we illustrate this feature with the definition of programming exercises as learning objects and its validation by the repository. The repository is also fully compliant with existing commu- nication standards and we propose extensions by adding new functions, formalizing message interchange and providing a REST interface. To validate the interoperability features of the repository, we developed a repository plug-in for Moodle that is expected to be included in the next release of this popular learning management system.

A type system for access control in an object-oriented language

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

CrimsonHex: a service oriented repository of specialised learning objects

The corner stone of the interoperability of eLearning systems is the standard definition of learning objects. Nevertheless, for some domains this standard is insufficient to fully describe all the assets, especially when they are used as input for other eLearning services. On the other hand, a standard definition of learning objects in not enough to ensure interoperability among eLearning systems; they must also use a standard API to exchange learning objects. This paper presents the design and implementation of a service oriented repository of learning objects called crimsonHex. This repository is fully compliant with the existing interoperability standards and supports new definitions of learning objects for specialized domains. We illustrate this feature with the definition of programming problems as learning objects and its validation by the repository. This repository is also prepared to store usage data on learning objects to tailor the presentation order and adapt it to learner profiles.

PETCHA: a Programming Exercises Teaching Assistant

This paper presents a tool called Petcha that acts as an automated Teaching Assistant in computer programming courses. The ultimate objective of Petcha is to increase the number of programming exercises effectively solved by students. Petcha meets this objective by helping both teachers to author programming exercises and students to solve them. It also coordinates a network of heterogeneous systems, integrating automatic program evaluators, learning management systems, learning object repositories and integrated programming environments. This paper presents the concept and the design of Petcha and sets this tool in a service oriented architecture for managing learning processes based on the automatic evaluation of programming exercises. The paper presents also a case study that validates the use of Petcha and of the proposed architecture.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.