Understanding Memories of the Past in the Context of Different Complex Neural Network Architectures

Deep learning (primarily using backpropagation) and neuroevolution are the preeminent methods of optimizing artificial neural networks. However, they often create black boxes that are as hard to understand as the natural brains they seek to mimic. Previous work has identified an information-theoretic tool, referred to as R, which allows us to quantify and identify mental representations in artificial cognitive systems. The use of such measures has allowed us to make previous black boxes more transparent. Here we extend R to not only identify where complex computational systems store memory about their environment but also to differentiate between different time points in the past. We show how this extended measure can identify the location of memory related to past experiences in neural networks optimized by deep learning as well as a genetic algorithm.

Operative communication: project Cybersyn and the intersection of information design, interface design, and interaction design

This article examines the connecting lines between the Chilean Project Cybersyn’s interface design, the German Hochschule für Gestaltung Ulm and its cybernetically inspired approaches towards information design, and later developments in interaction design and the emerging field of Human–Computer Interaction in the USA. In particular, it first examines how early works of designers Tomàs Maldonado and Gui Bonsiepe on operative communication, that is, language-independent (and thus internationalizable) pictogram systems and visual grammars for computational systems, were intertwined with attempts to ground industrial design in a scientific methodology, to address an era of computing machines, and to develop the concept of the interface as a heuristic for a renovated design thinking. It thereby also reconstructs further historical vanishing lines—e.g. the pictorial grammar of Otto Neurath’s ISOTYPE—of the development of the ‘ulm model’ of design. Second, the article explores how an apprehension of first-order cybernetics in West Germany—e.g. represented by hfg ulm staff like Max Bense or Abraham Moles, merged with Cybersyn’s second-order cybernetics ideas, as represented by Stafford Beer’s Viable System Model. And third, it asks about a further conceptual turn regarding an understanding of design which resulted in a focus on communicative interaction, e.g. in the later works of Fernando Flores and Terry Winograd on HCI, or in Beer’s Team Syntegrity approach. As an effect, the text will explore a specific and international network of cybernetic thinking between Latin America, Europe, and North America which emerged around Project Cybersyn, and which was occupied with questions of HCI, a democratization of design, and intelligence amplification.

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation1

The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the most prominent tools in the modelling of behaviour are computational-logic systems, connectionist models of cognition, and models of uncertainty. Recent studies in cognitive science, artificial intelligence, and psychology have produced a number of cognitive models of reasoning, learning, and language that are underpinned by computation. In addition, efforts in computer science research have led to the development of cognitive computational systems integrating machine learning and automated reasoning. Such systems have shown promise in a range of applications, including computational biology, fault diagnosis, training and assessment in simulators, and software verification. This joint survey reviews the personal ideas and views of several researchers on neural-symbolic learning and reasoning. The article is organised in three parts: Firstly, we frame the scope and goals of neural-symbolic computation and have a look at the theoretical foundations. We then proceed to describe the realisations of neural-symbolic computation, systems, and applications. Finally we present the challenges facing the area and avenues for further research.

Design of Socioenactive Systems Based on Physiological Sensors and Robot Behavior in Educational Environments

Computational systems based on ubiquitous and pervasive technology present several challenges related to the interaction of people with scenarios constituted by sensors and actuators, changing the mindset of what we used to understand as interaction with a computer. This also has influence in the ways of considering the design of systems based on contemporary technology for the educational context. To cope with the challenges of ubiquitous computing, the concept of socioenactive system is being constructed as a system in which human and technological aspects are coupled together in a cycle of perceptually guided actions of people interacting with elements of the physical environment and with other people in the same scenario. In this work we address the design of a socioenactive system as an evolution of two previous systems designed and experimented with 5-year-old children in an educational context. The contribution of this paper is twofold: 1. We present an analysis of two different systems tested in educational scenarios, pointing out the lack of elements that should be present in a complete cycle of socioenactive systems, suggesting requirements for a third system; 2. We present an architecture for the third system and a simulation of its usage. Results of the third system and its simulation inform the next activities of bringing it to real life in a practice proposed for the same audience and context as the previous systems.

Identification of Key Ischemic Stroke Genes by Computational Systems Biology

Stroke is one of the leading causes of death in humans. Even if patients survive from stroke, they may suffer sequelae such as disability. Treatment for strokes remains unsatisfactory due to an incomplete understanding of its mechanisms. This study investigates Ischemic Stroke (IS), a primary subtype of stroke, through analyses based on microarray data. Limma (in R)derives differentially expressed genes, and the protein-protein interaction (PPI) network is mapped from the database. Gene co-expression patterns are obtained for clustering gene modules by the Weighted Correlation Network Analysis (WGCNA), and genes with high connectivity in the significantly co-expressed modules are selected as key regulators. Common hubs are identified as Cdkn1a, Nes and Anxa2. Based on our analyses, we hypothesize that these hubs might play a key role in the onset and progression of IS. Result suggests the potential of identifying unexplored key regulators by the systemic method used in this work. Further analyses aim at expanding candidate genes for screening biomarkers for IS, and experimental validation is required on identified potential hubs.

Insect-Inspired Robots: Bridging Biological and Artificial Systems

This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.

In-Depth Verification of a Numerical Model for an Axisymmetric RC Dome

The designers of civil engineering structures often have to face the problem of the reliability of complex computational analyses performed most often with the Finite Element Method (FEM). Any assessment of reliability of such analyses is difficult and can only be approximate. The present paper puts forward a new method of verification and validation of the structural analyses upon an illustrative example of a dome strengthened by circumferential ribs along the upper and lower edges. Four computational systems were used, namely Abaqus, Autodesk Robot, Dlubal RFEM, and FEAS. Different models were also analyzed—two-dimensional (2D) and three-dimensional (3D) ones using continuum, bar, and shell finite elements. The results of the static (with two kinds of load—self-weight and load distributed along the upper ring) and modal analyses are presented. A detailed comparison between the systems’ and models’ predictions was made. In general, the spatial models predicted a less stiff behavior of the analyzed dome than the planar models. The good agreement between different models and systems was obtained for the first natural frequency with axisymmetric eigenmodes (except from the Autodesk Robot system). The presented approach to the verification of complex shell–bar models can be effectively applied by structural designers.