[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track最新文献
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11911
J. E. Kottemann, W. Remus
Arguing along several lines, G.P. Huber (1983) asserted that cognitive style should not be a basis for DSS (decision-support system) designed but that it may be useful in the development of training procedures. An experiment is described that tests these assertions using a production scheduling task. Results indicate that (1) by merely providing outcome feedback, individuals of all cognitive styles (as measured by the Myers-Briggs type indicator and risk preference) learned the task equally well; (2) cognitive style was useful in explaining performance differences during task learning but not thereafter; and (3) cognitive style did not predict the heuristics used but rather the consistency of their use; that is, the impact of cognitive style manifested as erratic decisions rather than systematic bias. These results are used to discuss the role of cognitive style in both training and design and to suggest reasons for the inconsistent results in cognitive style research.<>
{"title":"When and how cognitive style impacts decision-making","authors":"J. E. Kottemann, W. Remus","doi":"10.1109/HICSS.1988.11911","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11911","url":null,"abstract":"Arguing along several lines, G.P. Huber (1983) asserted that cognitive style should not be a basis for DSS (decision-support system) designed but that it may be useful in the development of training procedures. An experiment is described that tests these assertions using a production scheduling task. Results indicate that (1) by merely providing outcome feedback, individuals of all cognitive styles (as measured by the Myers-Briggs type indicator and risk preference) learned the task equally well; (2) cognitive style was useful in explaining performance differences during task learning but not thereafter; and (3) cognitive style did not predict the heuristics used but rather the consistency of their use; that is, the impact of cognitive style manifested as erratic decisions rather than systematic bias. These results are used to discuss the role of cognitive style in both training and design and to suggest reasons for the inconsistent results in cognitive style research.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123809017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11908
K. Kandt
The technical issues associated with supporting analysis tasks using computer-based tools are addressed. The objectives are to propose a framework for representing: (1) conceptual knowledge that supports model construction and manipulation; (2) arguments and the process of argumentation; and (3) time and calculi for reasoning with respect to time. In addition, techniques to reuse past analyses are discussed, as are issues involving man-machine communication. It is expected that this approach will lead to a tool that can support a number of disciplines by providing a generic capability for constructing models, managing information, and browsing through information.<>
{"title":"On building future decision support systems","authors":"K. Kandt","doi":"10.1109/HICSS.1988.11908","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11908","url":null,"abstract":"The technical issues associated with supporting analysis tasks using computer-based tools are addressed. The objectives are to propose a framework for representing: (1) conceptual knowledge that supports model construction and manipulation; (2) arguments and the process of argumentation; and (3) time and calculi for reasoning with respect to time. In addition, techniques to reuse past analyses are discussed, as are issues involving man-machine communication. It is expected that this approach will lead to a tool that can support a number of disciplines by providing a generic capability for constructing models, managing information, and browsing through information.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11917
H.-H. Chen
A notion, called knowledge development, for measuring the intelligence of machines is studied in the context of designing a versatile learning system. The notion is used in several ways: (1) it provides a guide to verify the overall intelligence of the expected machine, (2) it is claimed that an intelligently learning system should be able to assess the gain of intelligence level when a piece of knowledge is to be learned, and the notion can be used to address the feasibility of such an assessment and (3) it draws a justifiable boundary between the machine's responsibility and the user's responsibility. The base model of a general computing machine used is a Mealy finite state machine.<>
{"title":"A notion for machine learning: knowledge developability","authors":"H.-H. Chen","doi":"10.1109/HICSS.1988.11917","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11917","url":null,"abstract":"A notion, called knowledge development, for measuring the intelligence of machines is studied in the context of designing a versatile learning system. The notion is used in several ways: (1) it provides a guide to verify the overall intelligence of the expected machine, (2) it is claimed that an intelligently learning system should be able to assess the gain of intelligence level when a piece of knowledge is to be learned, and the notion can be used to address the feasibility of such an assessment and (3) it draws a justifiable boundary between the machine's responsibility and the user's responsibility. The base model of a general computing machine used is a Mealy finite state machine.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"64 2-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116845039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11933
J. E. Kottemann, D. Dolk
The authors outline a process-oriented approach to model integration based on familiar notions from discrete-event simulation and communicating sequential processes. They introduce features of a model integration command language (MICL) that incorporates message-passing, demons, suspend/resume mechanisms, and structured programming constructs to represent a model integration schema, or procedure. They present several examples of model integration from various domains or demonstrate how the MICL functions. The primary advantage of the MICL is that it allows model components to be used as building blocks for more elaborate composite models without necessitating modifications to the components themselves. Incorporating the MICL as part of a model-management system's model manipulation language provides a mechanism for multiparadigmatic integration as well as for assimilating behaviorally complex components, such as those found in discrete event simulation, into the model management framework.<>
{"title":"Process-oriented model integration","authors":"J. E. Kottemann, D. Dolk","doi":"10.1109/HICSS.1988.11933","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11933","url":null,"abstract":"The authors outline a process-oriented approach to model integration based on familiar notions from discrete-event simulation and communicating sequential processes. They introduce features of a model integration command language (MICL) that incorporates message-passing, demons, suspend/resume mechanisms, and structured programming constructs to represent a model integration schema, or procedure. They present several examples of model integration from various domains or demonstrate how the MICL functions. The primary advantage of the MICL is that it allows model components to be used as building blocks for more elaborate composite models without necessitating modifications to the components themselves. Incorporating the MICL as part of a model-management system's model manipulation language provides a mechanism for multiparadigmatic integration as well as for assimilating behaviorally complex components, such as those found in discrete event simulation, into the model management framework.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126061644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11905
Feng-Yi Kuo
An approach to integrating expert system models (for information regarding the present and future problem states) with a Bayesian forecasting model (for information based on the historical data) is presented. Using this approach, past, present, and future information can be processed coherently in an automated system to support forecasting in general. It is shown that this approach is a practical way to provide support to both qualitative and quantitative information processing.<>
{"title":"Combining expert systems and the Bayesian approach to support forecasting","authors":"Feng-Yi Kuo","doi":"10.1109/HICSS.1988.11905","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11905","url":null,"abstract":"An approach to integrating expert system models (for information regarding the present and future problem states) with a Bayesian forecasting model (for information based on the historical data) is presented. Using this approach, past, present, and future information can be processed coherently in an automated system to support forecasting in general. It is shown that this approach is a practical way to provide support to both qualitative and quantitative information processing.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122667308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11892
Shiv Kumar, Cheng Hsu
A framework of an intelligent forecasting assistant is developed. A detailed discussion is included of one component of this system, the selector, which is written in Lisp. The knowledge base of the system, the inference strategy, and the selection heuristic used are discussed.<>
{"title":"An expert system framework for forecasting method selection","authors":"Shiv Kumar, Cheng Hsu","doi":"10.1109/HICSS.1988.11892","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11892","url":null,"abstract":"A framework of an intelligent forecasting assistant is developed. A detailed discussion is included of one component of this system, the selector, which is written in Lisp. The knowledge base of the system, the inference strategy, and the selection heuristic used are discussed.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122697632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11926
J. Choobineh, J. Sena
The database language SQL is extended to allow the specification of constraints, computed attributes, triggers, and optimizations for mathematical linear programming problems. QSL can be used directly to interface with various linear optimization routines. In this regard, an integration of these models and databases, from a user point of view, is achieved. A macro architecture for the implementation of the system is proposed.<>
{"title":"A data sublanguage for formulation of linear mathematical models","authors":"J. Choobineh, J. Sena","doi":"10.1109/HICSS.1988.11926","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11926","url":null,"abstract":"The database language SQL is extended to allow the specification of constraints, computed attributes, triggers, and optimizations for mathematical linear programming problems. QSL can be used directly to interface with various linear optimization routines. In this regard, an integration of these models and databases, from a user point of view, is achieved. A macro architecture for the implementation of the system is proposed.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114316434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11884
J. Marsden, D. Pingry
Recent papers by G.P. Huber (1984) and by G.P. Huber and R. McDaniel (1986) have provided an excellent discussion of the forces that will determine the characteristics of the surviving firms in what is becoming known as the postindustrial age. Their picture of the organization of the future defines what has come to be known as the intelligent organization. The authors analyze and expand this concept of the intelligent organization. They utilize the framework developed in the Huber-McDaniel papers in combination with the traditional models of microeconomics to make several observations that they fell clarify some of the interactions between the design characteristics of a firm and its environment.<>
{"title":"The intelligent organization: some observations and alternative views","authors":"J. Marsden, D. Pingry","doi":"10.1109/HICSS.1988.11884","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11884","url":null,"abstract":"Recent papers by G.P. Huber (1984) and by G.P. Huber and R. McDaniel (1986) have provided an excellent discussion of the forces that will determine the characteristics of the surviving firms in what is becoming known as the postindustrial age. Their picture of the organization of the future defines what has come to be known as the intelligent organization. The authors analyze and expand this concept of the intelligent organization. They utilize the framework developed in the Huber-McDaniel papers in combination with the traditional models of microeconomics to make several observations that they fell clarify some of the interactions between the design characteristics of a firm and its environment.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130006979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11928
Marvin L Manheim
An architecture is proposed for decision-support systems that can provide active assistance to a user working on complex problems. The major feature is that, in addition to conventional user-directed processes, there are processes directed by a computer-directed-process manager (CDPM). For a CDPM to function, the system must maintain a continually updated model of what the user is doing. The input to this model is a history of the process, gathered by the history-recorder component of the system and analyzed by a history inference processor. Schema theory provides a framework construction of the model of the user problem-solving processes and the CDPM.<>
{"title":"An architecture for active DSS","authors":"Marvin L Manheim","doi":"10.1109/HICSS.1988.11928","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11928","url":null,"abstract":"An architecture is proposed for decision-support systems that can provide active assistance to a user working on complex problems. The major feature is that, in addition to conventional user-directed processes, there are processes directed by a computer-directed-process manager (CDPM). For a CDPM to function, the system must maintain a continually updated model of what the user is doing. The input to this model is a history of the process, gathered by the history-recorder component of the system and analyzed by a history inference processor. Schema theory provides a framework construction of the model of the user problem-solving processes and the CDPM.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124938127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HICSS.1988.11932
S. Bandyopahyay, A. Hevner
A box-structured methodology for solving business problems using available management science techniques is proposed. The procedure is free of bias caused by the choice of solution technique. Abstraction levels are developed for available management-science solution techniques. A mapping algorithm is defined that identifies what technique, or path of techniques, can be used to solve the problem. The abstraction categories are used in the decision process to narrow the search space of applicable techniques. The box-structured methodology supports the user evaluation of alternative solution techniques and provides a procedure for implementing the solution within an information system.<>
{"title":"A box structured methodology for solving business problems","authors":"S. Bandyopahyay, A. Hevner","doi":"10.1109/HICSS.1988.11932","DOIUrl":"https://doi.org/10.1109/HICSS.1988.11932","url":null,"abstract":"A box-structured methodology for solving business problems using available management science techniques is proposed. The procedure is free of bias caused by the choice of solution technique. Abstraction levels are developed for available management-science solution techniques. A mapping algorithm is defined that identifies what technique, or path of techniques, can be used to solve the problem. The abstraction categories are used in the decision process to narrow the search space of applicable techniques. The box-structured methodology supports the user evaluation of alternative solution techniques and provides a procedure for implementing the solution within an information system.<<ETX>>","PeriodicalId":339507,"journal":{"name":"[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track","volume":"320 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123407141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
[1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track
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