A Hybrid Decision Model for Improving Warehouse Efficiency in a Process-oriented View

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An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

A Dynamic Model of the Environmental Kuznets Curve : Turning Point and Public Poliy

We set up a simple dynamic macroeconomic model with (i) polluting consump- tion and a preference for a clean environment, (ii) increasing returns in abate- ment giving rise to an EKC and (iii) sustained growth resulting from a linear final-output technology. The model captures two sorts of market failures caused by external effects associated with consumption and environmental effort. This model is employed to investigate the determinants of the turning point and the (relative) effectiveness of different public policy measures aimed at a reduction of the environmental burden. Moreover, the model offers a potential explana- tion of an N-shaped pollution-income relation. Finally, it is shown that the model is compatible with most empirical regularities on economic growth and the environment.Environmental Kuznets Curve, Pollution, Abatement, External Ef- fects, Economic Growth, Public Policy

The (A)temporal Emergence of Spacetime

This paper examines two cosmological models of quantum gravity (from string theory and loop quantum gravity) to investigate the foundational and conceptual issues arising from quantum treatments of the big bang. While the classical singularity is erased, the quantum evolution that replaces it may not correspond to classical spacetime: it may instead be a non-spatiotemporal region, which somehow transitions to a spatiotemporal state. The different kinds of transition involved are partially characterized, the concept of a physical transition without time is investigated, and the problem of empirical incoherence for regions without spacetime is discussed.Comment: Forthcoming in Philosophy of Science; 13 page

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

The development of reasoning heuristics in autism and in typical development

Reasoning and judgment under uncertainty are often based on a limited number of simplifying heuristics rather than formal logic or rule-based argumentation. Heuristics are low-effort mental shortcuts, which save time and effort, and usually result in accurate judgment, but they can also lead to systematic errors and biases when applied inappropriately. In the past 40 years hundreds of papers have been published on the topic of heuristics and biases in judgment and decision making. However, we still know surprisingly little about the development and the cognitive underpinnings of heuristics and biases. The main aim of my thesis is to examine these questions. Another aim is to evaluate the applicability of dual-process theories of reasoning to the development of reasoning. Dual-process theories claim that there are two types of process underlying higher order reasoning: fast, automatic, and effortless (Type 1) processes (which are usually associated with the use of reasoning heuristics), and slow, conscious and effortful (Type 2) processes (which are usually associated with rule-based reasoning). This thesis presents eight experiments which investigated the development of reasoning heuristics in three different populations: typically developing children and adolescents between the age of 5 and 16, adolescents with autism, and university students. Although heuristic reasoning is supposed to be basic, simple, and effortless, we have found evidence that responses that are usually attributed to heuristic processes are positively correlated with cognitive capacity in the case of young children (even after controlling for the effects of age). Moreover, we have found that adolescents with autism are less susceptible to a number of reasoning heuristics than typically developing children. Finally, our experiments with university students provided evidence that education in statistics increases the likelihood of the inappropriate use of a certain heuristic (the equiprobability bias). These results offer a novel insight into the development of reasoning heuristics. Additionally, they have interesting implications for dual-process theories of reasoning, and they can also inform the debates about the rationality of reasoning heuristics and biases