84,406 research outputs found

    Constraint capture and maintenance in engineering design

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    The Designers' Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as Rolls-Royce, to ensure that the design is consistent with the specification for the particular design as well as with the company's design rule book(s). In the principal application discussed here, the evolving design is described against a jet engine ontology. Design rules are expressed as constraints over the domain ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a system, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. Further we hypothesize that in order to appropriately apply, maintain and reuse constraints, it is necessary to understand the underlying assumptions and context in which each constraint is applicable. We refer to them as “application conditions” and these form a part of the rationale associated with the constraint. We propose a methodology to capture the application conditions associated with a constraint and demonstrate that an explicit representation (machine interpretable format) of application conditions (rationales) together with the corresponding constraints and the domain ontology can be used by a machine to support maintenance of constraints. Support for the maintenance of constraints includes detecting inconsistencies, subsumption, redundancy, fusion between constraints and suggesting appropriate refinements. The proposed methodology provides immediate benefits to the designers and hence should encourage them to input the application conditions (rationales)

    Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness

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    This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas

    Decision-making and problem-solving methods in automation technology

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    The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming

    The virtual playground: an educational virtual reality environment for evaluating interactivity and conceptual learning

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    The research presented in this paper aims at investigating user interaction in immersive virtual learning environments (VLEs), focusing on the role and the effect of interactivity on conceptual learning. The goal has been to examine if the learning of young users improves through interacting in (i.e. exploring, reacting to, and acting upon) an immersive virtual environment (VE) compared to non interactive or non-immersive environments. Empirical work was carried out with more than 55 primary school students between the ages of 8 and 12, in different between-group experiments: an exploratory study, a pilot study, and a large-scale experiment. The latter was conducted in a virtual environment designed to simulate a playground. In this ‘Virtual Playground’, each participant was asked to complete a set of tasks designed to address arithmetical ‘fractions’ problems. Three different conditions, two experimental virtual reality (VR) conditions and a non-VR condition, that varied the levels of activity and interactivity, were designed to evaluate how children accomplish the various tasks. Pre-tests, post-tests, interviews, video, audio, and log files were collected for each participant, and analyzed both quantitatively and qualitatively. This paper presents a selection of case studies extracted from the qualitative analysis, which illustrate the variety of approaches taken by children in the VEs in response to visual cues and system feedback. Results suggest that the fully interactive VE aided children in problem solving but did not provide as strong evidence of conceptual change as expected; rather, it was the passive VR environment, where activity was guided by a virtual robot, that seemed to support student reflection and recall, leading to indications of conceptual change
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