Relevant bibliographies by topics / Expert heuristics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Expert heuristics'

Author: Grafiati
Published: 29 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Expert heuristics"

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Khowaja, Kamran, and Dena Al-Thani. "New Checklist for the Heuristic Evaluation of mHealth Apps (HE4EH): Development and Usability Study." JMIR mHealth and uHealth 8, no. 10 (October 28, 2020): e20353. http://dx.doi.org/10.2196/20353.

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Background Diabetes is one of the leading causes of death in developing countries. Existing mobile health (mHealth) app design guidelines lack a description of the support of continuous self-monitoring of health status, behavior change to improve and adopt a healthy lifestyle, and communication with health educators and health care professionals in case of any need. Objective This paper presents the development of a specialized set of heuristics called heuristic evaluation for mHealth apps (HE4EH) as an all-in-one tool and its applicability by performing a heuristic evaluation of an mHealth app. Methods An extensive review of heuristics and checklists was used to develop the HE4EH. The HE4EH was evaluated by domain experts for heuristics, checklist items, severity ratings, and overall satisfaction. The OneTouch app, which helps individuals with diabetes manage their blood glucose levels, was evaluated using HE4EH to identify usability problems that need to be fixed in the app. Results The expert evaluation of HE4EH revealed that the heuristics were important, relevant, and clear. The checklist items across the heuristics were clear, relevant, and acceptably grouped. In terms of evaluating the OneTouch app using the HE4EH, the most frequently violated heuristics included Content, Visibility, Match, and Self-monitoring. Most of the usability problems found were minor. The system usability scale score indicated that the OneTouch app is marginally acceptable. Conclusions This heuristic evaluation using the OneTouch app shows that the HE4EH can play a vital role for designers, researchers, and practitioners to use HE4EH heuristics and checklist items as a tool to design a new or evaluate and improve an existing mHealth app.
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Gonzaga de Oliveira, Sanderson L., and Libério M. Silva. "Low-cost heuristics for matrix bandwidth reduction combined with a Hill-Climbing strategy." RAIRO - Operations Research 55, no. 4 (July 2021): 2247–64. http://dx.doi.org/10.1051/ro/2021102.

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This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computations. Bandwidth optimization is a demanding subject for a large number of scientific and engineering applications. A heuristic for bandwidth reduction labels the rows and columns of a given sparse matrix. The algorithm arranges entries with a nonzero coefficient as close to the main diagonal as possible. This paper modifies an ant colony hyper-heuristic approach to generate expert-level heuristics for bandwidth reduction combined with a Hill-Climbing strategy when applied to matrices arising from specific application areas. Specifically, this paper uses low-cost state-of-the-art heuristics for bandwidth reduction in tandem with a Hill-Climbing procedure. The results yielded on a wide-ranging set of standard benchmark matrices showed that the proposed strategy outperformed low-cost state-of-the-art heuristics for bandwidth reduction when applied to matrices with symmetric sparsity patterns.
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Rassbach, Laura, Elizabeth Bradley, and Ken Anderson. "Providing Decision Support for Cosmogenic Isotope Dating." AI Magazine 32, no. 2 (March 16, 2011): 69. http://dx.doi.org/10.1609/aimag.v32i2.2349.

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Human experts in scientific fields routinely work with evidence that is noisy and untrustworthy, heuristics that are unproven, and possible conclusions that are contradictory. We present a deployed AI system, Calvin, for cosmogenic isotope dating, a domain that is fraught with these difficult issues. Calvin solves these problems using an argumentation framework and a system of confidence that uses two-dimensional vectors to express the quality of heuristics and the applicability of evidence. The arguments it produces are strikingly similar to published expert arguments. Calvin is in daily use by isotope dating experts.
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Frank, Lukas, Rouven Poll, Maximilian Roeglinger, and Rupprecht Lea. "Design heuristics for customer-centric business processes." Business Process Management Journal 26, no. 6 (March 22, 2020): 1283–305. http://dx.doi.org/10.1108/bpmj-06-2019-0257.

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PurposeCustomer centricity has evolved into a success factor for many companies, requiring all corporate activities – including business processes – to be aligned with customer needs. With most existing approaches to business process (re-)design focusing on process efficiency, customers are often treated as second-class citizens. Despite emergent research on customer process management, there is a lack of guidance on how to design customer-centric business processes.Design/methodology/approachThe authors conducted a structured literature review and analyzed companies awarded for outstanding customer centricity to compile design heuristics for customer-centric business processes. The authors iteratively validated and refined these heuristics with experts from academia and industry. Finally, the heuristics was grouped according to their expected impact on interaction capabilities to enable their prioritization in specific settings.FindingsThe authors proposed 15 expert-approved and literature-backed design heuristics for customer-centric business processes together with real-world examples. The heuristics aim at increasing customer satisfaction with interaction-intensive core processes, which is an important driver of corporate success.Originality/valueThe design heuristics complement existing efficiency-centered (re-)design heuristics. They reflect cognitive shortcuts that support process analysts in the generation of innovative ideas during process (re-)design. The heuristics also add to customer process management and help put customer centricity into practice.
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Chow, K. C. Ander, and W. E. Watt. "A knowledge-based expert system for flood frequency analysis." Canadian Journal of Civil Engineering 17, no. 4 (August 1, 1990): 597–609. http://dx.doi.org/10.1139/l90-068.

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Single-station flood frequency analysis is an important element in hydrotechnical planning and design. In Canada, no single statistical distribution has been specified for floods; hence, the conventional approach is to select a distribution based on its fit to the observed sample. This selection is not straightforward owing to typically short record lengths and attendant sampling error, magnified influence of apparent outliers, and limited evidence of two populations. Nevertheless, experienced analysts confidently select a distribution for a station based only on a few heuristics. A knowledge-based expert system has been developed to emulate these expert heuristics. It can perform data analyses, suggest an appropriate distribution, detect outliers, and provide means to justify a design flood on physical grounds. If the sample is too small to give reliable quantile estimates, the system performs a Bayesian analysis to combine regional information with station-specific data. The system was calibrated and tested for 52 stations across Canada. Its performance was evaluated by comparing the distributions selected by experts with those given by the developed system. The results indicated that the system can perform at an expert level in the task of selecting distributions. Key words: flood frequency, expert system, single-station, fuzzy logic, inductive reasoning, production system.
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Mehrez, A., and G. Steinberg. "Rule-Based Expert System versus Novices' Heuristics: A Matching Identification Problem." Psychological Reports 82, no. 3_suppl (June 1998): 1423–31. http://dx.doi.org/10.2466/pr0.1998.82.3c.1423.

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The present study focused on encoding and retrieval of knowledge as aids to decision-making by comparing the performance of rule-based expert systems and novices' heuristics within the framework of a matching identification problem. A rule-based expert system is developed with a computerized controlled procedure to evaluate and compare its performance with search strategies employed by novices. Analysis indicated that, as problem size increased, the system's outcome compared to novices' heuristics is improved.
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CHAN, CHRISTINE WAICHI, WEERAPONG KRITPIPHAT, and PAITOON TONTIWACHWUTHIKUL. "KNOWLEDGE ENGINEERING OF A MONITORING AND CONTROL DECISION SUPPORT SYSTEM." International Journal of Software Engineering and Knowledge Engineering 10, no. 03 (June 2000): 301–18. http://dx.doi.org/10.1142/s0218194000000183.

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This paper presents the Object-Oriented Knowledge Engineering (OOKE) methodology and its application in developing an expert system. OOKE is an expert system development methodology which incorporates the conceptual modelling tool of Inferential Modelling Technique into the analysis model of the Object-Oriented Software Engineering methodology. It was applied to develop a supervisory and decision support system for monitor and control of a water distribution system called the Water Advisor. The expertise, heuristics and reasoning knowledge of experts were acquired and then formulated in a model building process using the OOKE into a conceptual model which became the basis for a prototype expert system.
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Dobre, Jolie, Craig Harrington, Jennifer Herout, Charlene Weir, Ashley Cook, Tippy Carter, Donna Baggetta, and Walter “Bud” Relihan. "Rapid Heuristic Evaluation: Ensuring Fast and Reliable Usability Support." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 610–14. http://dx.doi.org/10.1177/1541931213601638.

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The U.S. Department of Veterans Affairs (VA) Human Factors Engineering (HFE) office developed a usability testing method called “Rapid Heuristic Evaluation” (Rapid HE) that offers benefits to users of the Agile development process. Rapid HE addresses the need to combine fast, reliable usability support with feedback from clinical subject matter experts (SMEs) during the design and development of an electronic health record (EHR). The Rapid HE process leverages established EHR heuristics to accelerate wireframe review and approval, and merges a traditional heuristic evaluation (HE) with an expert review by two SMEs. Our application of Rapid HEs has maximized use of resources and minimized the amount of time needed to provide feedback during Agile development cycles. This paper describes the Rapid HE process, deviations from traditional HEs, and reports on data from 16 HEs that our group conducted on an EHR platform currently being developed by VA.
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Barai, Sudhikumar, and Padmesh Charan Pandey. "KNOWLEDGE BASED EXPERT SYSTEM APPROACH TO INSTRUMENTATION SELECTION (INSEL)." TRANSPORT 19, no. 4 (August 31, 2004): 171–76. http://dx.doi.org/10.3846/16484142.2004.9637971.

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The selection of appropriate instrumentation for any structural measurement of civil engineering structure is a complex task. Recent developments in Artificial Intelligence (AI) can help in an organized use of experiential knowledge available on instrumentation for laboratory and in‐situ measurement. Usually, the instrumentation decision is based on the experience and judgment of experimentalists. The heuristic knowledge available for different types of measurement is domain dependent and the information is scattered in varied knowledge sources. The knowledge engineering techniques can help in capturing the experiential knowledge. This paper demonstrates a prototype knowledge based system for INstrument SELection (INSEL) assistant where the experiential knowledge for various structural domains can be captured and utilized for making instrumentation decision. In particular, this Knowledge Based Expert System (KBES) encodes the heuristics on measurement and demonstrates the instrument selection process with reference to steel bridges. INSEL runs on a microcomputer and uses an INSIGHT 2+ environment.
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Beyer, F., D. Schneider, and A. Schumacher. "Finding three-dimensional layouts for crashworthiness load cases using the graph and heuristic based topology optimization." Structural and Multidisciplinary Optimization 63, no. 1 (November 14, 2020): 59–73. http://dx.doi.org/10.1007/s00158-020-02768-0.

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AbstractIn this paper we present a new procedure using the graph and heuristic based topology optimization in order to find layouts for three-dimensional frame structures under crash loads. A three-dimensional graph describes the geometry and is used to derive a finite element shell model. The model of the frame structure consists of different profiles with continuous cross-sections. The ends of the profiles are currently rigidly connected. Each cross-section is defined by an individual two-dimensional graph. After performing a simulation its results are used by competing heuristics to propose new topologies for the frame structure. Most of these heuristics are derived from expert knowledge. Over several iterations, the goal is to improve the structures mechanical behavior. Typical objectives are the minimization of the structural intrusion in a crash scenario or the minimization of the maximal contact force between structural components. The presented method includes topology optimization by heuristics and shape optimization respectively sizing by mathematical optimization algorithms. The new flexible syntax for three- and two-dimensional graphs, the optimization process and the currently used heuristics are described. The performance is demonstrated for two examples, each optimized twice with opposing objectives.
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Dissertations / Theses on the topic "Expert heuristics"

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Smith, Susan N. "Teaching Analysis to Professional Writing Students: Heuristics Based on Expert Theories." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194794.

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Professional writing students must analyze communications in multiple modalities, on page or screen. This project argues that student analysts benefit from using articulated heuristics, summaries of articles, books, or theories in chart form that remain in the visual field with the communication to be analyzed. Keeping the heuristic in view reduces students' cognitive load by narrowing the search for solution to the categories in the heuristic. These heuristics, often one page or one screen, contain key words, phrases, or questions that allow students to approach analysis from experts' points of view at more than one level of complexity. Students locate instantiations of the categories in the communication analyzed, incorporating the category/instantiation pairs into personal schemas for analysis. As students classify communications, relate parts together and to other communications, and perform operations on the content, they see how communication achieves its meaning and formulate appropriate responses. Rather than rely on one all-purpose heuristic, this dissertation presents a range of heuristics reflecting rhetorical, discourse, linguistic, usability, and visual strategies that enable students to critique both form and function in communication. The heuristics reflect a systematically ordered workplace context, articulate an appropriate and specific theory for the situation, interface with other heuristic systems for depth and efficacy, and instantiate the categories at some helpful secondary level of complexity. To theorize the visual nature of the heuristic chart displays, I employ the semiotic of Charles Sanders Peirce, working through the implications of chart construction as I diagram Peirce's theory of diagrammatic iconicity.
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Machac, Mary Kristin. "A Model of Expert Instructional Design Heuristics Incorporating Design Thinking Methods." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/102926.

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Novice instructional designers have limited experience working with ill-structured problems, and often do not possess the mental models to effectively analyze, manage, and communicate the overall design process of new instructional design projects (Wedman and Tessmer, 1993; Rowland, 1992; Perez and Emery, 1995; Liu, Gibby, Quiros, and Demps, 2002). In their 2016 article of expert instructional design principles applied by experienced designers in practice, York and Ertmer proposed the following questions for future research, "(a) Can we teach principles to novice instructional designers? (b) What methods should we use to provide this information?" (York and Ertmer, 2016, p. 189). This research further explored these questions and offers a new model of expert instructional design heuristics incorporating design thinking methods. The purpose of this study was to identify design thinking methods that aligned with heuristics of expert instructional design practitioners, and to design and develop a new model of heuristics and design thinking methods, which could assist novice instructional designers as they enter the instructional design field. The literature outlines challenges reported among novice instructional designers throughout the instructional design process, which includes their ability to solve ill-structured problems; conduct thorough analyses; collaborate in teams; negotiate priorities; generate a variety of ideas for solutions; overcome resource, budget and time constraints; communicate and manage projects with stakeholders; and prototype, iterate and pilot new design solutions (Rowland, 1992; Hoard, Stefaniak, Baaki, and Draper, 2019; Roytek, 2010; Liu, Gibby, Quiros, and Demps, 2002; Chang and Kuwata, 2020; Tracey and Boling, 2014; Perez and Emery, 1995; Williams van Rooij, 1993). The model offers novice instructional designers specific methods and combinations of methods to use for every stage of the instructional design process. As instructional designers implement design thinking methods within the context of their daily situations, they should become more comfortable and begin to adapt the methods to meet their individual needs for each stage of their process.
Doctor of Philosophy
Instructional design is a system of procedures for developing education and training curricula in a consistent and reliable fashion (Branch and Merrill, 2011; Branch and Kopcha, 2014). It embodies an iterative process for outlining outcomes, selecting teaching and learning strategies, choosing support technologies, identifying media, and measuring performance (Branch and Kopcha, 2014). Instructional designers use models of instructional design and instructional development to communicate tasks and procedures of the instructional design process (Andrews and Goodson, 1980). Over the years, numerous models of instructional design have been developed and adapted to meet the varying needs of instructional designers and developers. There is a consensus that most instructional processes consist of five core elements or stages: analysis, design, development, implementation, and evaluation, which are commonly referred to as ADDIE (Seels and Glasgow, 1990; Branch and Kopcha, 2014). While often considered generic, the ADDIE framework contains a useful set of common criteria, which most designers state as important or necessary as a part of any instructional design process (Pittenger, Janke, and Bumgardner, 2009; York and Ertmer, 2011; 2016). Novice instructional designers have limited experience working with ill-structured problems, and often do not possess the mental models (prior experience) to effectively analyze, manage, and communicate the overall design process of new instructional design projects (Wedman and Tessmer, 1993; Rowland, 1992; Perez and Emery, 1995; Liu, Gibby, Quiros, and Demps, 2002). In their 2016 article of expert instructional design principles applied by experienced designers in practice, York and Ertmer proposed the following questions for future research, "(a) Can we teach principles to novice instructional designers? (b) What methods should we use to provide this information?" (York and Ertmer, 2016, p. 189). This research further explored these questions and offers a new model of expert instructional design heuristics incorporating design thinking methods. For this study, heuristics were defined as generalized stages of an instructional designer's process and design thinking was defined as a human-centered design process for solving complex problems. The purpose of this study was to identify design thinking methods that aligned with heuristics of expert instructional design practitioners, and to design and develop a new model of heuristics and design thinking methods, which could assist novice instructional designers as they enter the instructional design field. The literature outlines challenges reported among novice instructional designers throughout the instructional design process, which includes their ability to solve ill-structured problems; conduct thorough analyses; collaborate in teams; negotiate priorities; generate a variety of ideas for solutions; overcome resource, budget and time constraints; communicate and manage projects with stakeholders; and prototype, iterate and pilot new design solutions (Rowland, 1992; Hoard, Stefaniak, Baaki, and Draper, 2019; Roytek, 2010; Liu, Gibby, Quiros, and Demps, 2002; Chang and Kuwata, 2020; Tracey and Boling, 2014; Perez and Emery, 1995; Williams van Rooij, 1993). The model offers novice instructional designers specific methods and combinations of methods to use for every stage of the instructional design process. As instructional designers implement design thinking methods within the context of their daily situations, they should become more comfortable and begin to adapt the methods to meet their individual needs for each stage of their process.
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Lim, Hedy. "Discovering expert instructional designers' heuristics for creating scenario-based workplace instruction." Thesis, Capella University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10103202.

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Scenario-based instructional design is ideal for workplace training, as it promotes practical and performance-based learning through the use of realistic situations. The research problem is a need for well-defined heuristics, what Gibbons (2014) called operational principles and what York and Ertmer (2011) called rules of thumb, being basic guidelines that promote and characterize expertise, in the area of scenario-based online instruction. The purpose of this Delphi study was to gather expert feedback on ideas in the form of a set of best practices for scenario-based online instructional design for the workplace. The research questions break down the topic into four basic areas: identifying a learning problem, discovering scaffolds or learning resources, maintaining project momentum, and essential concerns for instructional development. Experts in workplace scenario-based instructional design, with particular emphasis on professionals with an online or academic presence, were recruited as subjects. A detailed review of the literature gathered forty-two original statements that were organized into five categories. Per Delphi methodology, the study was conducted as a three round iterative online instrument. Subjects were asked to rate each statement and to provide additional statements to clarify and expand on their best practices based on their experience. Twenty-nine subjects completed all three rounds of the research study. While the statements express a wide variety of best practices for the field, recommendations for further research generally focused on thoughtful consideration of the learner, the instructional development team, and a focus on the integrity or realistic authenticity of the learning scenario, throughout the instructional experience.

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Cheam, T. S. "Expert systems and heuristics in rota design : With reference to hospital staffing." Thesis, University of Strathclyde, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381513.

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Stuckart, Daniel W. "Secondary students using expert heuristics in the analysis of digitalized historical documents." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000232.

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Szarek, Harmony Kristin. "Subjectivity in Expert Decision Making: Risk Assessment, Acceptability, and Cognitive Heuristics Affecting Endangered Species Act Listing Judgments for the Greater Yellowstone Ecosystem Grizzly Bear." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1430998102.

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Ahmad, Abdul-Rahim. "An Intelligent Expert System for Decision Analysis and Support in Multi-Attribute Layout Optimization." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/785.

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Layout Decision Analysis and Design is a ubiquitous problem in a variety of work domains that is important from both strategic and operational perspectives. It is largely a complex, vague, difficult, and ill-structured problem that requires intelligent and sophisticated decision analysis and design support.

Inadequate information availability, combinatorial complexity, subjective and uncertain preferences, and cognitive biases of decision makers often hamper the procurement of a superior layout configuration. Consequently, it is desirable to develop an intelligent decision support system for layout design that could deal with such challenging issues by providing efficient and effective means of generating, analyzing, enumerating, ranking, and manipulating superior alternative layouts.

We present a research framework and a functional prototype for an interactive Intelligent System for Decision Support and Expert Analysis in Multi-Attribute Layout Optimization (IDEAL) based on soft computing tools. A fundamental issue in layout design is efficient production of superior alternatives through the incorporation of subjective and uncertain design preferences. Consequently, we have developed an efficient and Intelligent Layout Design Generator (ILG) using a generic two-dimensional bin-packing formulation that utilizes multiple preference weights furnished by a fuzzy Preference Inferencing Agent (PIA). The sub-cognitive, intuitive, multi-facet, and dynamic nature of design preferences indicates that an automated Preference Discovery Agent (PDA) could be an important component of such a system. A user-friendly, interactive, and effective User Interface is deemed critical for the success of the system. The effectiveness of the proposed solution paradigm and the implemented prototype is demonstrated through examples and cases.

This research framework and prototype contribute to the field of layout decision analysis and design by enabling explicit representation of experts? knowledge, formal modeling of fuzzy user preferences, and swift generation and manipulation of superior layout alternatives. Such efforts are expected to afford efficient procurement of superior outcomes and to facilitate cognitive, ergonomic, and economic efficiency of layout designers as well as future research in related areas.

Applications of this research are broad ranging including facilities layout design, VLSI circuit layout design, newspaper layout design, cutting and packing, adaptive user interfaces, dynamic memory allocation, multi-processor scheduling, metacomputing, etc.
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Sandström, Kristian. "A study of the iOS : An exploratory article on how large of a role the iOS has played in the success of the iPhone." Thesis, Umeå universitet, Institutionen för informatik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-45210.

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The iPhone has become a top selling smartphone since its launch in 2007 and has along with its iOS (Apple's mobile operating system) overtaken many popular and established mobile phone brands in the ratings. Some competitors have not been able to provide a competing smartphone while others have grouped together to withstand the Apple onslaught. There are probably quite a few reasons why the iPhone has become such a success, and one could likely write a report solely about those reasons. I will focus on one of them in this study, maybe one of the most important reasons: the iPhone came with a revolutionizing user interface. I have studied iOS applications and their user interface components along with related research in order to try and find out what exactly makes it so attractive and also to uncover any flaws I might stumble across along the way. In order to answer this, and to gain a better insight into the iOS, I have developed an iPhone application from scratch covering all of the basic functionality usually found in any other iPhone application. The results will show that most of it seems to relate with Apple enforcing very strict rules and guidelines, along with limitations placed on the developer and the process as a whole. This strict process ends with Apple evaluators performing a review of the finished product, using their guidelines as heuristics. These guidelines will be proven to have scientific credibility, and the controlled development process will be a key to defining the iOS success.
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Lewis, John N. "Expert systems development utilizing heuristic methods." Thesis, Monterey, California. Naval Postgraduate School, 1996. http://hdl.handle.net/10945/8376.

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Approved for public release; distribution is unlimited.
This thesis analyzes the diagnostic domain and isolates the heuristics employed by experts to arrive at diagnostic solutions. These heuristic methods are then generalized in order to arrive at a series of heuristic rules that can be applied to a wide range of diagnostic processes independent of there respective domain. To test the validity of the generalized heuristics, a prototype expert system was created targeting the heuristics employed by avionics repair technicians in repair of the APS- 1 15 radar system on the P-3C Orion.
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Park, SangHee. "Inoculation Information Against Contagious Disease Misperception about Flu with Heuristic vs. Systematic Information and Expert vs. Non-Expert Source." Bowling Green State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1446827113.

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Books on the topic "Expert heuristics"

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Clancey, William J. Heuristic classification. [Alexandria, Va.]: DTIC, 1985.

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Lewis, John N. Expert systems development utilizing heuristic methods. Monterey, Calif: Naval Postgraduate School, 1996.

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Luca, Console, ed. Diagnostic problem solving: Combining heuristic, approximate and causal reasoning. (London): North Oxford Academic, 1989.

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Torasso, Pietro. Diagnostic problem solving: Combining heuristic, approximate and casual reasoning. [London]: North Oxford Academic, 1989.

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Luca, Console, ed. Diagnostic problem solving: Combining heuristic, approximate, and causal reasoning. New York: Van Nostrand Reinhold, 1989.

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Lowe, S. Knowledge acquisition for expert systems: A preliminary investigation into the heuristics of online searching. 1987.

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Boden, Margaret A. 2. General intelligence as the Holy Grail. Oxford University Press, 2018. http://dx.doi.org/10.1093/actrade/9780199602919.003.0002.

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A host of state-of-the-art AI applications exist, designed for countless specific tasks and used in almost every area of life, by laymen and professionals alike. Many outperform even the most expert humans. In that sense, progress has been spectacular. But the AI pioneers were also hoping for systems with general intelligence. ‘General intelligence as the Holy Grail’ explains why artificial general intelligence is still highly elusive despite recent increases in computer power. It considers the general AI strategies in recent research—heuristics, planning, mathematical simplification, and different forms of knowledge representation—and discusses the concepts of the frame problem, agents and distributed cognition, machine learning, and generalist systems.
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Expert Systems Development Utilizing Heuristic Methods. Storming Media, 1996.

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Peters, Ellen. Overcoming Innumeracy and the Use of Heuristics When Communicating Science. Edited by Kathleen Hall Jamieson, Dan M. Kahan, and Dietram A. Scheufele. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190497620.013.42.

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Science communication is difficult because, rather than understanding and using important, often numeric, information, lay people and experts alike resort to superficial heuristic processing of information. This chapter examines heuristic processing with respect to the power of experience, the affect heuristic, and framing effects along with their interactions with innumeracy. Recommendations are made for how to improve science communication to decrease use of heuristic processing and improve use of numeric information in risk perceptions and decision making. Based on existing evidence, science communicators should carefully identify communication goals and then choose evidence-based strategies to meet them. Evidence-based strategies include providing numeric information (as opposed to not providing it), reducing cognitive effort, increasing affective meaning, and drawing attention to key information.
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Yeh, Chune-Sin. An expert system approach to the optimal design of single-junction and multijunction tandem solar cells. 1988.

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Book chapters on the topic "Expert heuristics"

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Sindre, Guttorm, Even-André Karlsson, and Patricia Paul. "Heuristics for Maintaining Term Structures for Relaxed Search." In Database and Expert Systems Applications, 20–25. Vienna: Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-7557-6_4.

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van den Herik, H. J., J. C. Stoop, and P. R. Varkevisser. "Heuristics in the Abbot-Monk Problem." In Expert Systems and Artificial Intelligence in Decision Support Systems, 175–95. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3805-2_10.

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Van de Merckt, Thierry. "ILISCE: A system for learning control heuristics in a scheduling environment." In Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 471–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/bfb0024999.

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Kurihara, Masahito, and Hisashi Kondo. "Heuristics and Experiments on BDD Representation of Boolean Functions for Expert Systems in Software Verification Domains." In Advanced Topics in Artificial Intelligence, 353–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-46695-9_30.

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Puppe, Frank. "Heuristic Classification." In Systematic Introduction to Expert Systems, 131–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77971-8_15.

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Puppe, Frank. "Heuristic Classification: Additional Mechanisms." In Systematic Introduction to Expert Systems, 149–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77971-8_16.

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Console, Luca, Luigi Portinale, Daniele Theseider Dupré, and Pietro Torasso. "Combining Heuristic Reasoning with Causal Reasoning in Diagnostic Problem Solving." In Second Generation Expert Systems, 46–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-77927-5_3.

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Mathur, Priyanka. "Heuristic Expert Evaluation of e-Learning Application." In Rising Threats in Expert Applications and Solutions, 155–62. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6014-9_18.

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Nguyen-Phu, Hao. "Prolog Language — CADSD Package Interfacing Procedures: Applications to Heuristic Identification and Control of Dynamic Systems." In Expert Systems and Robotics, 243–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76465-3_14.

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Binder, Thomas. "Computer Assisted Generation of Heuristic Rules in the Management of Cardiac Arrhythmias." In Expert Systems and Decision Support in Medicine, 322–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-48706-4_50.

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Conference papers on the topic "Expert heuristics"

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Joseph, Earl C. "Management by heuristics expert systems." In the conference. New York, New York, USA: ACM Press, 1987. http://dx.doi.org/10.1145/24533.24539.

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Fillingim, Kenton B., Richard Ossie Nwaeri, Felipe Borja, Katherine Fu, and Christiaan J. J. Paredis. "Design Heuristics: Analysis and Synthesis From Jet Propulsion Laboratory’s Architecture Team." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85584.

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This study offers insight into the processes of expert designers at the Jet Propulsion Laboratory (JPL) and how they make use of heuristics in the design process. A methodology for the extraction, classification, and characterization of heuristics is presented. Ten expert participants were interviewed to identify design heuristics used during early stage space mission design at JPL. In total, 101 heuristics were obtained, classified, and characterized. Through the use of postinterview surveys, participants characterized heuristics based on attributes including source/origin, applicability based on concept maturity, frequency of use, reliability, and tendency to evolve. These findings are presented, and statistically analyzed to show correlations between the participant perceptions of frequency of use, reliability, and evolution of a heuristic. Survey results and analysis aim to identify valid attributes for assessing the applicability and value of multiple heuristics for design practice in early space mission formulation.
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Väätäjä, Heli, Jari Varsaluoma, Tomi Heimonen, Katariina Tiitinen, Jaakko Hakulinen, Markku Turunen, Harri Nieminen, and Petri Ihantola. "Information Visualization Heuristics in Practical Expert Evaluation." In the Beyond Time and Errors. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2993901.2993918.

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Da Costa, Paulo, Yingqian Zhang, Alp Akcay, and Uzay Kaymak. "Learning 2-opt Local Search from Heuristics as Expert Demonstrations." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533697.

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Blösch-Paidosh, Alexandra, and Kristina Shea. "Preliminary User Study on Design Heuristics for Additive Manufacturing." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85908.

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Additive manufacturing (AM) has unique capabilities when compared to traditional manufacturing, such as shape, hierarchical, functional, and material complexity, a fact that has fascinated those in research, industry, and the media for the last decade. Consequently, designers would like to know how they can incorporate AM’s special capabilities into their designs, but are often at a loss as to how to do so. Design for Additive Manufacturing (DfAM) methods are currently in development but the vast majority of existing methods are not tailored to the needs and knowledge of designers in the early stages of the design a process. The authors have previously derived 29 design heuristics for AM. In this paper, the efficacy of these heuristics is tested in the context of a re-design scenario with novice designers. The preliminary results show that the heuristics positively influence the designs generated by the novice designers. Analysis of the use of specific heuristics by the participants and future research to validate the impact of the design heuristics for additive manufacturing with expert designers and in original design scenarios is planned.
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Ellsworth, R., A. Parkinson, and F. Cain. "The Complementary Roles of Symbolic Computing and Numerical Optimization in Engineering Design Software." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0010.

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Abstract In many engineering design problems, the designer converges upon a good design by iteratively evaluating a mathematical model of the design problem. The trial-and-error method used by the designer to converge upon a solution may be complex and difficult to capture in an expert system. It is suggested that in many cases, the design rule base could be made significantly smaller and more maintainable by using numerical optimization methods to identify the best design. The expert system is then used to define the optimization problem and interpret the solution, as well as to apply the true heuristics to the problem. An example of such an expert system is presented for the design of a valve anti-cavitation device. Because of the capabilities provided by the optimization software, the expert system has been able to outperform the expert in the test cases evaluated so far.
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Kota, S., A. G. Erdman, D. R. Riley, A. Esterline, and J. R. Slagle. "An Expert System for Initial Selection of Dwell Linkages." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0051.

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Abstract Dwell linkages have numerous applications in industry, especially in automation. Traditional use of more expensive cams is due to lack of proper design tools for synthesizing dwell linkages. By systematically and extensively studying entire motion characteristics of hundreds of linkages, a comprehensive classification system and heuristics were developed. This qualitative classification scheme led to a finite set of linkage models that cover the entire design space in the sense that any possible design falls under one or more of the models. Our system, called Dwell-Expert, incorporates design expertise to select the best linkage model for a given set of design specifications and to compare that model against alternatives. This new design methodology and its implementation in AGNESS (A Generalized Network-based Expert System Shell) are explained. A design example is presented. Our system can reduce even an experienced designer’s initial-design time from a day or more to a minute or less, assuming specifications have already been formulated. Such results motivate extension of this design methodology to other areas of mechanical design and engineering design in general.
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Hart, P. K., and J. Rodriguez. "A Dual-Purpose KBES for Preliminary Structural Design." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0092.

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Abstract A prototype expert system for automatic preliminary shape synthesis is being developed. The purpose of this system is to generate preliminary designs which can be used either for basic engineering or as an initial solution in an optimization scheme. The developed prototype intends to emulate the conceptual-design/preliminary-redesign phases in the design process. Both phases have been modularized and developed under adequate computational shells. Modules requiring heuristic support are implemented in a LISP/KEE™ environment, the ones being computer-intensive are in C subroutines. Heuristics are applied in the initial design phase to produce an adequate definition of the geometric domain. For the redesign phase, a set of options were programmed into the inference mechanism. These rules focus on molding the geometric domain. Rules for the inference mechanism, and common databases were elaborated. The two-dimensional problems of a fillet in a tension bar, and a connecting link are used to illustrate the system. This is part of an ongoing project at the Center for Computer Aids for Industrial Productivity (CAIP) in New Jersey.
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Djurdjanovic, Dragan, and Jun Ni. "Measurement Scheme Synthesis in Multi-Station Machining Systems." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32865.

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The selection of measurements in multi-station machining systems is currently not a systematic process and it involves expert human intervention. In this paper, the recently introduced formal methods for quantitative characterization of measurement schemes in multi-station machining systems are employed in devising systematic measurement scheme synthesis procedures. The newly proposed synthesis procedures were applied in devising measurement schemes in the process used to machine a car engine cylinder head. It was observed that the measurement scheme synthesis procedure based on a genetic algorithm robustly outperformed the synthesis procedures based on the heuristics of successive measurement removal.
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Roy, Rajkumar, Ian C. Parmee, and Graham Purchase. "Qualitative Evaluation of Engineering Designs Using Fuzzy Logic." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1449.

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Abstract The paper describes a Qualitative Evaluation System developed using a fuzzy expert system. The evaluation system gives a qualitative rating to design solutions by considering manufacturability aspects, choice of materials and some special preferences. The information is used in decision support for engineering design. The system is an integrated part of a decision support tool for engineering design called the ‘Adaptive Search Manager’ (ASM). ASM uses an adaptive search technique to identify multiple design solutions for a 12 dimensional Turbine Blade Cooling System design problem. Thus the task has been to develop a fuzzy expert system that can qualitatively evaluate any design solution from a design space using a realistically small number of fuzzy rules. The developed system utilises a knowledge separation and then a knowledge integration technique. The design knowledge is first separated into three categories: inter variable knowledge, intra variable knowledge and heuristics. Inter variable knowledge and intra variable knowledge are integrated using a concept of “compromise”. The qualitative evaluation system can evaluate any design solution within the 12 dimensional design space, but uses only 44 fuzzy rules and one function that implements the inter variable knowledge.
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