An approach is presented to the optimization of decision trees. A decision tree is considered optimal if it correctly classifies the known data set and has the minimal number of nodes. It is shown that it is important to decide the right order of attributes to test, for this can reduce the number of checking nodes in a decision tree.<>
{"title":"Optimization of the decision tree","authors":"W. Jung, J. B. Jones, Jianhua Chen","doi":"10.1109/TAI.1991.167043","DOIUrl":"https://doi.org/10.1109/TAI.1991.167043","url":null,"abstract":"An approach is presented to the optimization of decision trees. A decision tree is considered optimal if it correctly classifies the known data set and has the minimal number of nodes. It is shown that it is important to decide the right order of attributes to test, for this can reduce the number of checking nodes in a decision tree.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126774838","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}
A method for representing texts describing biological systems is presented. The representation is that which an educated layman would build from reading a text describing a biological system. This representation is viewed as a bridge between the English description of a biological system and deeper representations of such a system. The representation is based on temporal relations which are used to index and organize knowledge about biological systems (circulatory, respiratory, etc.) in a hierarchy of events. Several reasoning methods which the proposed representation permits are explained. A method for drawing diagrams depicting the function of the systems represented is also included.<>
{"title":"Representing biological and physical systems as temporal event hierarchies","authors":"F. Gomez","doi":"10.1109/TAI.1991.167092","DOIUrl":"https://doi.org/10.1109/TAI.1991.167092","url":null,"abstract":"A method for representing texts describing biological systems is presented. The representation is that which an educated layman would build from reading a text describing a biological system. This representation is viewed as a bridge between the English description of a biological system and deeper representations of such a system. The representation is based on temporal relations which are used to index and organize knowledge about biological systems (circulatory, respiratory, etc.) in a hierarchy of events. Several reasoning methods which the proposed representation permits are explained. A method for drawing diagrams depicting the function of the systems represented is also included.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121575254","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}
A generalized scheduling development environment allows a person who composes schedules to specify both an application and a methodology, in developing a scheduling program. The authors have designed such a system and have built a proof-of-concept prototype. The prototype has been tested on two fairly different application examples. It demonstrates the expressive capability of logic programming in representing the diversity of the two examples, and it exemplifies a method of achieving generality in the domain of scheduling.<>
{"title":"Generalized scheduling development environment","authors":"W. Fabens, L. Sterling","doi":"10.1109/TAI.1991.167050","DOIUrl":"https://doi.org/10.1109/TAI.1991.167050","url":null,"abstract":"A generalized scheduling development environment allows a person who composes schedules to specify both an application and a methodology, in developing a scheduling program. The authors have designed such a system and have built a proof-of-concept prototype. The prototype has been tested on two fairly different application examples. It demonstrates the expressive capability of logic programming in representing the diversity of the two examples, and it exemplifies a method of achieving generality in the domain of scheduling.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120897104","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}
N. Bourbakis, Robin Williams, F. Golshani, M. Flickner, T. Laliotis, Sukhan Lee, J. Delgado-Frías, D. Hammerstrom, C. Koutsougeras, G. Pechanek, B. Wah, J. Yen, F. Bastani, Tom Cooper, K. Harbison-Briggs, R. Lauber, A. Preece, I. Zualkernan, W. Tsai, D. Cooke, M. Feather, S. Fickas, N. Minsky, P. Selfridge, Douglas Smith
In this panel session, the following topics are discussed: artificial intelligence in business; artificial intelligence in multimedia; neural networks as a tool for artificial intelligence: software engineering for knowledge-based systems: and artificial intelligence as a solution for software engineering.<>
{"title":"AI in multimedia (panel session)","authors":"N. Bourbakis, Robin Williams, F. Golshani, M. Flickner, T. Laliotis, Sukhan Lee, J. Delgado-Frías, D. Hammerstrom, C. Koutsougeras, G. Pechanek, B. Wah, J. Yen, F. Bastani, Tom Cooper, K. Harbison-Briggs, R. Lauber, A. Preece, I. Zualkernan, W. Tsai, D. Cooke, M. Feather, S. Fickas, N. Minsky, P. Selfridge, Douglas Smith","doi":"10.1109/TAI.1991.167067","DOIUrl":"https://doi.org/10.1109/TAI.1991.167067","url":null,"abstract":"In this panel session, the following topics are discussed: artificial intelligence in business; artificial intelligence in multimedia; neural networks as a tool for artificial intelligence: software engineering for knowledge-based systems: and artificial intelligence as a solution for software engineering.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121662634","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}
The authors have developed a constraint-based method of describing features. Every feature is controlled by geometric constraints, which naturally specify the dimensioning information that reflects the designer's intent. An ATMS-based geometric reasoning system is proposed that efficiently evaluates the constraints in order to determine geometric attributes, and detects over-constrained situations in order to resolve conflicts among the constraints.<>
{"title":"An ATMS-based geometric constraint solver for 3D CAD","authors":"Shuichi Shimizu, Keisuke Inoue, M. Numao","doi":"10.1109/TAI.1991.167106","DOIUrl":"https://doi.org/10.1109/TAI.1991.167106","url":null,"abstract":"The authors have developed a constraint-based method of describing features. Every feature is controlled by geometric constraints, which naturally specify the dimensioning information that reflects the designer's intent. An ATMS-based geometric reasoning system is proposed that efficiently evaluates the constraints in order to determine geometric attributes, and detects over-constrained situations in order to resolve conflicts among the constraints.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131389323","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}
A fast hypothetical reasoning system is described which is named KICK-SHOTGAN, and which avoids inefficient backtracking by the forward synthesis of necessary hypothesis combination along this network. The formation of inference-path network is based on a linear-time algorithm for the satisfiability testing of propositional Horn clauses. This system differs from ATMS mainly in its total problem solving nature. That is, it works for the logical problem-solving framework which yields a solution for a given goal, whereas the ATMS calculates possible data supported by hypotheses incrementally in response to the input of a justification (rule) from a problem solver existing outside the ATMS.<>
{"title":"Fast hypothetical reasoning system using inference-path network","authors":"M. Ishizuka, Fumiaki Ito","doi":"10.1109/TAI.1991.167115","DOIUrl":"https://doi.org/10.1109/TAI.1991.167115","url":null,"abstract":"A fast hypothetical reasoning system is described which is named KICK-SHOTGAN, and which avoids inefficient backtracking by the forward synthesis of necessary hypothesis combination along this network. The formation of inference-path network is based on a linear-time algorithm for the satisfiability testing of propositional Horn clauses. This system differs from ATMS mainly in its total problem solving nature. That is, it works for the logical problem-solving framework which yields a solution for a given goal, whereas the ATMS calculates possible data supported by hypotheses incrementally in response to the input of a justification (rule) from a problem solver existing outside the ATMS.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132861813","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}
A prototype system known as IRENE (intelligent reverse engineering environment), for acquiring business concepts from Cobol programs is described. It is a workbench used for experimenting with a novel approach to acquiring business knowledge embedded in software systems. The system's acquisition mechanisms rely on the availability of semantic (domain) knowledge about two kinds of relationships among concepts known as derivations and determinations.<>
{"title":"Automated business knowledge acquisition from programs","authors":"V. Karakostas","doi":"10.1109/TAI.1991.167074","DOIUrl":"https://doi.org/10.1109/TAI.1991.167074","url":null,"abstract":"A prototype system known as IRENE (intelligent reverse engineering environment), for acquiring business concepts from Cobol programs is described. It is a workbench used for experimenting with a novel approach to acquiring business knowledge embedded in software systems. The system's acquisition mechanisms rely on the availability of semantic (domain) knowledge about two kinds of relationships among concepts known as derivations and determinations.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115630276","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}
An examination is made of the fundamental trade-off between exploration and exploitation in a genetic algorithm (GA). An immigration operator is introduced that infuses random members into successive GA populations. It is theorized that immigration maintains much of the exploitation of the GA while increasing exploration. To test this theory, a set of functions that often require the GA to perform an excessive number of evaluations to find the global optimum of the function is designed. For These functions, it is shown experimentally that a GA enhanced with immigration (1) reduces the number of trials that require an excessive number of evaluations and (2) decreases the average number of evaluations needed to find the optimum function.<>
{"title":"Reducing the search time of a steady state genetic algorithm using the immigration operator","authors":"M. C. Moed, Charles V. Stewart, R. Kelley","doi":"10.1109/TAI.1991.167032","DOIUrl":"https://doi.org/10.1109/TAI.1991.167032","url":null,"abstract":"An examination is made of the fundamental trade-off between exploration and exploitation in a genetic algorithm (GA). An immigration operator is introduced that infuses random members into successive GA populations. It is theorized that immigration maintains much of the exploitation of the GA while increasing exploration. To test this theory, a set of functions that often require the GA to perform an excessive number of evaluations to find the global optimum of the function is designed. For These functions, it is shown experimentally that a GA enhanced with immigration (1) reduces the number of trials that require an excessive number of evaluations and (2) decreases the average number of evaluations needed to find the optimum function.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121944598","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}
Genetic algorithms have been used to solve parameter optimization problems and for machine learning. Basic genetic algorithm concepts are introduced. The authors discuss genetic algorithm applications, and present results of a project to develop a software tool-a genetic algorithm programming environment-called Splicer.<>
{"title":"A genetic algorithm programming environment: Splicer","authors":"Steven E. Bayer, Lui Wang","doi":"10.1109/TAI.1991.167088","DOIUrl":"https://doi.org/10.1109/TAI.1991.167088","url":null,"abstract":"Genetic algorithms have been used to solve parameter optimization problems and for machine learning. Basic genetic algorithm concepts are introduced. The authors discuss genetic algorithm applications, and present results of a project to develop a software tool-a genetic algorithm programming environment-called Splicer.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122089024","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}
The iterative development life cycle (IDLC) provides a management process for the successful development of large-scale intelligent system applications. The iterative process minimizes both risks and costs by combining both the well structured management techniques of the waterfall process and the early validation techniques of the evolutionary model. This process is more adaptable to the full range of software project situations and provides the flexibility necessary to accommodate a high dynamic range of technical alternatives.<>
{"title":"Iterative development life cycle (IDLC): a management process for large scale intelligent system development","authors":"F. Miller, Rosemarie J. Paradis, Kevin Whalen","doi":"10.1109/TAI.1991.167042","DOIUrl":"https://doi.org/10.1109/TAI.1991.167042","url":null,"abstract":"The iterative development life cycle (IDLC) provides a management process for the successful development of large-scale intelligent system applications. The iterative process minimizes both risks and costs by combining both the well structured management techniques of the waterfall process and the early validation techniques of the evolutionary model. This process is more adaptable to the full range of software project situations and provides the flexibility necessary to accommodate a high dynamic range of technical alternatives.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126631889","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}
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