A Robotic Solution for the Restoration of Fresco Paintings

In this paper, a service robot solution is presented for the analysis, surveying and restoration of fresco paintings. The proposed design approach integrates robot design and restoration operation. It aims to merge them into a feasible solution that can be both practical and feasible for restorers. The simulation results are reported to show a successful design solution, which has been conceived with the constraints of a low-cost user-oriented design and the consideration of cultural heritage

Turing learning: : A metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for 'tricking' the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product - the classifiers - that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.Comment: camera-ready versio

Research Agenda into Human-Intelligence/Machine-Intelligence Governance

Since the birth of modern artificial intelligence (AI) at the 1956 Dartmouth Conference, the AI community has pursued modeling and coding of human intelligence into AI reasoning processes (HI Þ MI). The Dartmouth Conference\u27s fundamental assertion was that every aspect of human learning and intelligence could be so precisely described that it could be simulated in AI. With the exception of knowledge specific areas (such as IBM\u27s Big Blue and a few others), sixty years later the AI community is not close to coding global human intelligence into AI. In parallel, the knowledge management (KM) community has pursued understanding of organizational knowledge creation, transfer, and management (HI Þ HI) over the last 40 years. Knowledge management evolved into an organized discipline in the early 1990\u27s through formal university courses and creation of the first chief knowledge officer organizational positions. Correspondingly, over the last 25 years there has been growing research into the transfer of intelligence and cooperation among computing systems and automated machines (MI Þ MI). In stark contrast to the AI community effort, there has been little research into transferring AI knowledge and machine intelligence into human intelligence (MI Þ HI) with a goal of improving human decision making. Most important, there has been no research into human-intelligence/machine-intelligence decision governance; that is, the policies and processes governing human-machine decision making toward systemic mission accomplishment. To address this gap, this paper reports on a research initiative and framework toward developing an HI-MI decision governance body of knowledge and discipline

A critique of contemporary artificial intelligence art: Who is Edmond de Belamy?

Edmond de Belamy is a 2018 painting made by french collective Obvious, created using a type of Artificial Intelligence algorithms called Generative Adversarial Networks, which was sold at Christie's auction house in New York for $432,500. This historic event -the so-called auction of the "first artwork made by an AI" raises 3 interesting questions about authorship, originality, and the arts as a space for scientific inquiry. While some think that the current deployment of Machine Learning algorithms and Artificial Intelligence techniques that we are seeing in the art world today may be seen as the ultimate "Gesamtkunstwerk" or total artwork, other points of view express that not only we need this type of cultural artifacts as a critique of industrialized use of Artificial Intelligence, but also a strict criteria has to be delimited in order to review contemporary art made with Machine Learning techniques

Biologically inspired digital fabrication

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 37-40).Objects and systems in nature are models for the practice of sustainable design and fabrication. From trees to bones, natural systems are characterized by the constant interplay of creation, environmental response, and analysis of current structural constituents, as part of a larger dynamic system. In contrast, traditional methods of digital design and fabrication are characterized by a linear progression of three main stages: modeling (digital generation in the digital domain), analysis (digital mapping of the physical domain), and fabrication (physical generation of the digital domain). Moving towards a system process where modeling, analysis, and fabrication are integrated together for the development of a dynamic process will transform traditional fabrication technology and bring about the creation of sustainable and more efficient synthetic environments. Integration of modeling, analysis, and fabrication into one fluid process requires the development of a fabrication platform with capabilities for real time control. This thesis explores and investigates the creation of a framework for real time control of industrial robotic arms as part of a multipurpose fabrication platform.by Sarah Han.M. Eng

Art and Medicine: A Collaborative Project Between Virginia Commonwealth University in Qatar and Weill Cornell Medicine in Qatar

Four faculty researchers, two from Virginia Commonwealth University in Qatar, and two from Weill Cornell Medicine in Qatar developed a one semester workshop-based course in Qatar exploring the connections between art and medicine in a contemporary context. Students (6 art / 6 medicine) were enrolled in the course. The course included presentations by clinicians, medical engineers, artists, computing engineers, an art historian, a graphic designer, a painter, and other experts from the fields of art, design, and medicine. To measure the student experience of interdisciplinarity, the faculty researchers employed a mixed methods approach involving psychometric tests and observational ethnography. Data instruments included pre- and post-course semi-structured audio interviews, pre-test / post-test psychometric instruments (Budner Scale and Torrance Tests of Creativity), observational field notes, self-reflective blogging, and videography. This book describes the course and the experience of the students. It also contains images of the interdisciplinary work they created for a culminating class exhibition. Finally, the book provides insight on how different fields in a Middle Eastern context can share critical /analytical thinking tools to refine their own professional practices

Robot Heavens and Robot Dreams: Ultimate Reality in A.I. and Other Recent Films

Numerous recent films understand ultimate reality to be multi-layered. This article examines the various formulas films use to express this idea, such as heaven, dreams, technology, temporal loops and altered mental states, while also exploring the various religious and philosophical traditions on which these ultimate reality films draw. Next, I suggest a postmodern framework as a way of accounting for the ubiquity of the reality theme across filmic genres and I argue that film is a unique medium for expressing this epistemology. Finally, I turn to an extensive analysis of A.I. as a case study of a postmodern, multivalent ultimate reality film and illuminate nine possible endings that combine myth, religion, Freud and Jung with themes of technology and ontological identity