A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.Comment: 12 pages,55 reference

NASA Ames potential flow analysis (POTFAN) geometry program (POTGEM), version 1

A computer program known as POTGEM is reported which has been developed as an independent segment of a three-dimensional linearized, potential flow analysis system and which is used to generate a panel point description of arbitrary, three-dimensional bodies from convenient engineering descriptions consisting of equations and/or tables. Due to the independent, modular nature of the program, it may be used to generate corner points for other computer programs

Decimal to Binary Number Conversion can be Fun

Numbering systems are of great importance in Computer Science and Engineering education. The binary numbering system can be considered as one of the most fundamental, since its understanding is essential for the understanding of other Computer Science and Engineering concepts, such as data representation, data storage, computer architecture, networking, and many more. Yet, students are having difficulties understanding it. One approach which has been shown to improve learning of different science and mathematics concepts is the use of educational games. Educational games have the potential to engage and motivate learners through fun activities. This paper presents a small exploratory survey on an electronic educational game for practicing decimal to binary number conversions

Ethical and Social Aspects of Self-Driving Cars

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.Comment: 11 pages, 3 figures, 2 table

Artificial Intellignce: Art or Science?

Computer programs are new kinds of machines with great potential for improving the quality of life. In particular, expert systems could improve the ability of the small, weak and poor members of society to access the information they need to solve their problems. However, like most areas of computing, expert systems design is currently practiced as an art. In order to realise its potential it must also become an engineering science: providing the kinds of assurances of reliability that are normal in other branches of engineering. The way to do this is to put the techniques used to build expert systems and other artificial intelligence programs onto a sound theoretical foundation. The tools of mathematical logic appear to be a good basis for doing this, but we need to be imaginative in their use-not restricting ourselves to the kind of deductive reasoning usually thought of as 'logical', but investigating other aspects of reasoning, including uncertain reasoning, making conjectures and the guidance of inference. Acknow ledgement