Pub Date : 2003-05-01DOI: 10.1109/TSMCC.2003.815954
J.Z. Zhang, Q.M.J. Wu, W. Gruver
William A. Gruver (F’96) received the B.S.E.E, M.S.E.E and Ph.D. degrees in electrical engineering from the University of Pennsylvania in 1963, 1966 and 1970, repectively; and the DIC in Automatic Control Systems from Imperial College of Science and Technology, London, in 1965. He is Professor of Engineering Science as Simon Fraser University in Burnaby, British Columbia, Canada. His industrial experience includes management and technical leadership positions at GE’s Fac-
William A. Gruver, 1996年毕业，分别于1963年、1966年和1970年获得宾夕法尼亚大学电气工程学士学位、硕士学位和博士学位;1965年获得伦敦帝国理工学院自动控制系统学士学位。他是加拿大不列颠哥伦比亚省本拿比的西蒙弗雷泽大学工程科学教授。他的行业经验包括在GE的face -担任管理和技术领导职务
{"title":"Correction to \"Binocular transfer method for point-feature tracking of image sequences\"","authors":"J.Z. Zhang, Q.M.J. Wu, W. Gruver","doi":"10.1109/TSMCC.2003.815954","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.815954","url":null,"abstract":"William A. Gruver (F’96) received the B.S.E.E, M.S.E.E and Ph.D. degrees in electrical engineering from the University of Pennsylvania in 1963, 1966 and 1970, repectively; and the DIC in Automatic Control Systems from Imperial College of Science and Technology, London, in 1965. He is Professor of Engineering Science as Simon Fraser University in Burnaby, British Columbia, Canada. His industrial experience includes management and technical leadership positions at GE’s Fac-","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"9 1","pages":"291"},"PeriodicalIF":0.0,"publicationDate":"2003-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87770987","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 : 2003-05-01DOI: 10.1109/TSMCC.2003.813151
E. Gargouri, S. Hammadi
Workshop scheduling problems can be considered as one of the main factors to improve the productivity and efficiency of a manufacturing system. The continuous evolution and the dynamic characteristics of industrial workshops, particularly those of agro-food industries, impose the generation of a real time decision scheduling process. In the agro-food industries, the products to be processed and the used primary products are characterized by their limit validity dates which generate some particularly and especially antagonist criteria. A distributed decision support system for real time scheduling is described in this paper. It is based on an original cooperative approach aimed to elaborate robust decisions that propose to the "best action" to the decision maker. The decision process is distributed all along the production chain. At each decision time, in order to ensure coherency, we have to take into account the neighborhood constraints in order to simultaneously satisfy different criteria which do not have the same importance. An aggregation criteria system is defined to manage the criteria among their importance degrees. We define a decisional model based on the evaluation and the comparison of a set of proposed actions.
{"title":"A distributed scheduling for agro-food manufacturing problems","authors":"E. Gargouri, S. Hammadi","doi":"10.1109/TSMCC.2003.813151","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.813151","url":null,"abstract":"Workshop scheduling problems can be considered as one of the main factors to improve the productivity and efficiency of a manufacturing system. The continuous evolution and the dynamic characteristics of industrial workshops, particularly those of agro-food industries, impose the generation of a real time decision scheduling process. In the agro-food industries, the products to be processed and the used primary products are characterized by their limit validity dates which generate some particularly and especially antagonist criteria. A distributed decision support system for real time scheduling is described in this paper. It is based on an original cooperative approach aimed to elaborate robust decisions that propose to the \"best action\" to the decision maker. The decision process is distributed all along the production chain. At each decision time, in order to ensure coherency, we have to take into account the neighborhood constraints in order to simultaneously satisfy different criteria which do not have the same importance. An aggregation criteria system is defined to manage the criteria among their importance degrees. We define a decisional model based on the evaluation and the comparison of a set of proposed actions.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"2 1","pages":"176-185"},"PeriodicalIF":0.0,"publicationDate":"2003-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83826007","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 : 2003-05-01DOI: 10.1109/TSMCC.2003.813149
H. Darabi, Mohsen A. Jafari, S. S. Manapure
Despite the efforts in scheduling and control of flexible manufacturing systems (FMSs) with resource constraints, the current pool of scheduling techniques faces two major drawbacks: modeling and complexity. Modeling is the task of converting the FMS data to a set of information, ready to be processed by a scheduling algorithm. Complexity has a direct relation with the amount of effort required to execute a scheduling algorithm successfully on the information set generated in the modeling phase. In this paper, we use finite automata (FA) theory to develop a modeling formalism and its accompanying scheduling algorithm for control and scheduling of FMS with resource constraints. While the FA-based modeling is completely automatic and does not need any human-designer interference, its related algorithm is both effective and efficient. We use IDEF3 standard to capture the FMS activities and resource data. We propose a three-step procedure. In the first step, the IDEF3 data set is converted to a finite automaton, preserving the activity precedence relationships. In the second step, the resulted finite automaton is decomposed to smaller (in size) scheduling problems that can be independently optimized. In the third step, a heuristic scheduling algorithm is used to handle each problem separately. We applied the developed procedure to 100 problems. The results are satisfactory and promising.
{"title":"Finite automata decomposition for flexible manufacturing systems control and scheduling","authors":"H. Darabi, Mohsen A. Jafari, S. S. Manapure","doi":"10.1109/TSMCC.2003.813149","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.813149","url":null,"abstract":"Despite the efforts in scheduling and control of flexible manufacturing systems (FMSs) with resource constraints, the current pool of scheduling techniques faces two major drawbacks: modeling and complexity. Modeling is the task of converting the FMS data to a set of information, ready to be processed by a scheduling algorithm. Complexity has a direct relation with the amount of effort required to execute a scheduling algorithm successfully on the information set generated in the modeling phase. In this paper, we use finite automata (FA) theory to develop a modeling formalism and its accompanying scheduling algorithm for control and scheduling of FMS with resource constraints. While the FA-based modeling is completely automatic and does not need any human-designer interference, its related algorithm is both effective and efficient. We use IDEF3 standard to capture the FMS activities and resource data. We propose a three-step procedure. In the first step, the IDEF3 data set is converted to a finite automaton, preserving the activity precedence relationships. In the second step, the resulted finite automaton is decomposed to smaller (in size) scheduling problems that can be independently optimized. In the third step, a heuristic scheduling algorithm is used to handle each problem separately. We applied the developed procedure to 100 problems. The results are satisfactory and promising.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"55 1","pages":"168-175"},"PeriodicalIF":0.0,"publicationDate":"2003-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86746536","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809347
Xiao-Jun Zeng, M. Singh
This paper presents the knowledge bounded least squares method that uses both linguistic information (i.e., human knowledge and experience) and numerical data to identify fuzzy models. Based on the concept of fuzzy interval systems, the basic idea of this method is: first, to utilize all the available linguistic information to obtain a fuzzy interval system and then use the obtained fuzzy interval system to give the admissible model set (i.e., the set of all fuzzy models which are acceptable and reasonable from the point of view of linguistic information); second, to find a fuzzy model in the admissible fuzzy model set which best fits the available numerical data. It is shown that such a fuzzy model can be obtained by a quadratic programming approach. By comparing this method with the least squares method, it is proved that the fuzzy model obtained by the proposed method fits the real model better than the fuzzy model obtained by the least squares method.
{"title":"Knowledge bounded least squares method for the identification of fuzzy systems","authors":"Xiao-Jun Zeng, M. Singh","doi":"10.1109/TSMCC.2003.809347","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809347","url":null,"abstract":"This paper presents the knowledge bounded least squares method that uses both linguistic information (i.e., human knowledge and experience) and numerical data to identify fuzzy models. Based on the concept of fuzzy interval systems, the basic idea of this method is: first, to utilize all the available linguistic information to obtain a fuzzy interval system and then use the obtained fuzzy interval system to give the admissible model set (i.e., the set of all fuzzy models which are acceptable and reasonable from the point of view of linguistic information); second, to find a fuzzy model in the admissible fuzzy model set which best fits the available numerical data. It is shown that such a fuzzy model can be obtained by a quadratic programming approach. By comparing this method with the least squares method, it is proved that the fuzzy model obtained by the proposed method fits the real model better than the fuzzy model obtained by the least squares method.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"46 1","pages":"24-32"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74736974","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809867
Yifei Xue, Donald E. Brown
Crime analysis uses past crime data to predict future crime locations and times. Typically this analysis relies on hot spot models that show clusters of criminal events based on past locations of these events. It does not consider the decision making processes of criminals as human initiated events susceptible to analysis using spatial choice models. This paper analyzes criminal incidents as spatial choice processes. Spatial choice analysis can be used to discover the distribution of people's behaviors in space and time. Two adjusted spatial choice models that include models of decision making processes are presented. The comparison results show that adjusted spatial choice models provide efficient and accurate predictions of future crime patterns and can be used as the basis for a law enforcement decision support system. This paper also extends spatial choice modeling to include the class of problems where the decision makers' preferences are derived indirectly through incident reports rather than directly through survey instruments.
{"title":"A decision model for spatial site selection by criminals: a foundation for law enforcement decision support","authors":"Yifei Xue, Donald E. Brown","doi":"10.1109/TSMCC.2003.809867","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809867","url":null,"abstract":"Crime analysis uses past crime data to predict future crime locations and times. Typically this analysis relies on hot spot models that show clusters of criminal events based on past locations of these events. It does not consider the decision making processes of criminals as human initiated events susceptible to analysis using spatial choice models. This paper analyzes criminal incidents as spatial choice processes. Spatial choice analysis can be used to discover the distribution of people's behaviors in space and time. Two adjusted spatial choice models that include models of decision making processes are presented. The comparison results show that adjusted spatial choice models provide efficient and accurate predictions of future crime patterns and can be used as the basis for a law enforcement decision support system. This paper also extends spatial choice modeling to include the class of problems where the decision makers' preferences are derived indirectly through incident reports rather than directly through survey instruments.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"26 1","pages":"78-85"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81845458","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809355
P. Borne, B. Fayech, S. Hammadi, S. Maouche
This paper deals with the real-time regulation of traffic within a disrupted transportation system. We outline the necessity of a decision support system that detects, analyzes, and resolves the unpredicted disturbances. Due to the distributed aspects of transportation systems, we present a multi-agent approach for the regulation process. Moreover, this approach also includes an evolutionary algorithm that is based on an original genetic coding representing the decisions on a set of vehicles and stops affected by the disturbance. This set constitutes, in fact, the space-time horizon of the regulation process. The evolutionary algorithm then treats the regulation problem as an optimization and provides the regulator with relevant decisions that can result in a partial reconfiguration of the network.
{"title":"Decision support system for urban transportation networks","authors":"P. Borne, B. Fayech, S. Hammadi, S. Maouche","doi":"10.1109/TSMCC.2003.809355","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809355","url":null,"abstract":"This paper deals with the real-time regulation of traffic within a disrupted transportation system. We outline the necessity of a decision support system that detects, analyzes, and resolves the unpredicted disturbances. Due to the distributed aspects of transportation systems, we present a multi-agent approach for the regulation process. Moreover, this approach also includes an evolutionary algorithm that is based on an original genetic coding representing the decisions on a set of vehicles and stops affected by the disturbance. This set constitutes, in fact, the space-time horizon of the regulation process. The evolutionary algorithm then treats the regulation problem as an optimization and provides the regulator with relevant decisions that can result in a partial reconfiguration of the network.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"24 1","pages":"67-77"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78541513","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809871
J. Neidhoefer, C. Cox, R. Saeks
The focus of this paper is to describe a neural adaptive control (NAC) technology derived using a Lyapunov synthesis technique. The NAC is a nonlinear adaptive controller which requires minimal plant information. It adapts its gains in real time to maintain the desired performance and to automatically compensate for changes in plant dynamics caused by system failures, environmental changes, or component damage. As such, the NAC control technology has the potential to enhance system performance by automatically optimizing its control laws for each operating regime. It can also increase reliability by automatically compensating for plant damage and system failures.
{"title":"Development and application of a Lyapunov synthesis based neural adaptive controller","authors":"J. Neidhoefer, C. Cox, R. Saeks","doi":"10.1109/TSMCC.2003.809871","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809871","url":null,"abstract":"The focus of this paper is to describe a neural adaptive control (NAC) technology derived using a Lyapunov synthesis technique. The NAC is a nonlinear adaptive controller which requires minimal plant information. It adapts its gains in real time to maintain the desired performance and to automatically compensate for changes in plant dynamics caused by system failures, environmental changes, or component damage. As such, the NAC control technology has the potential to enhance system performance by automatically optimizing its control laws for each operating regime. It can also increase reliability by automatically compensating for plant damage and system failures.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"40 1","pages":"125-136"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89788295","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809345
J. Tien
The focus of this paper is on decision making; more specifically, on what decision making requirements are needed in the future. We augur for a decision informatics paradigm; it is a real-time, information-based approach to decision making. The paradigm is supported by two sets of technologies (i.e., information and decision technologies) and underpinned by three disciplines (i.e., data fusion/analysis, decision modeling, and systems engineering). We begin by considering the context - and needs - for decision making as the economies of the world change and evolve, especially in regard to emerging services; then our proposed decision informatics paradigm is detailed and illustrated, together with an in-depth review of a critical, underpinning research area (dealing with real-time fusion and analysis of multiple nonhomogeneous data sources), followed by several concluding remarks.
{"title":"Toward a decision informatics paradigm: a real-time, information-based approach to decision making","authors":"J. Tien","doi":"10.1109/TSMCC.2003.809345","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809345","url":null,"abstract":"The focus of this paper is on decision making; more specifically, on what decision making requirements are needed in the future. We augur for a decision informatics paradigm; it is a real-time, information-based approach to decision making. The paradigm is supported by two sets of technologies (i.e., information and decision technologies) and underpinned by three disciplines (i.e., data fusion/analysis, decision modeling, and systems engineering). We begin by considering the context - and needs - for decision making as the economies of the world change and evolve, especially in regard to emerging services; then our proposed decision informatics paradigm is detailed and illustrated, together with an in-depth review of a critical, underpinning research area (dealing with real-time fusion and analysis of multiple nonhomogeneous data sources), followed by several concluding remarks.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"20 1","pages":"102-113"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TSMCC.2003.809345","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72403941","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809350
J. Palmer, A. Sage, T. Sheridan, M. H. Smith, J. Tien
In the evolution of any professional organization, it is informative and desirable to take stock of what has occurred, and to use this assessment to consider and plan for the future. The IEEE Systems, Man, and Cybernetics (SMC) Society is considered to be the leading professional society in the transdisciplinary area of systems engineering, cybernetics, and human machine systems, and has an international reputation for our efforts in developing and presenting innovative research results related to this area. In this paper, we - group of five current and former SMC Society presidents - consider the past, present, and future of the IEEE SMC Society; we are also doing this to commemorate the Society's 30th anniversary. In particular, we address our auspicious beginning; our transition from an incubatee to an incubator society; the breadth of our transactions; the international character of our membership; the appropriateness of our name; the move toward an "intelligent" systems-oriented umbrella organization; the evolving array of research areas; and the challenges and opportunities we face in the future.
{"title":"The IEEE Systems, Man, and Cybernetics Society: historical development, current status, and future perspectives","authors":"J. Palmer, A. Sage, T. Sheridan, M. H. Smith, J. Tien","doi":"10.1109/TSMCC.2003.809350","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809350","url":null,"abstract":"In the evolution of any professional organization, it is informative and desirable to take stock of what has occurred, and to use this assessment to consider and plan for the future. The IEEE Systems, Man, and Cybernetics (SMC) Society is considered to be the leading professional society in the transdisciplinary area of systems engineering, cybernetics, and human machine systems, and has an international reputation for our efforts in developing and presenting innovative research results related to this area. In this paper, we - group of five current and former SMC Society presidents - consider the past, present, and future of the IEEE SMC Society; we are also doing this to commemorate the Society's 30th anniversary. In particular, we address our auspicious beginning; our transition from an incubatee to an incubator society; the breadth of our transactions; the international character of our membership; the appropriateness of our name; the move toward an \"intelligent\" systems-oriented umbrella organization; the evolving array of research areas; and the challenges and opportunities we face in the future.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"256 1","pages":"13-23"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74534646","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 : 2003-02-01DOI: 10.1109/TSMCC.2003.809361
L. Fang, K. Hipel, D. Kilgour, Xiaoyong Peng
A comprehensive decision support system, GMCR II, is developed for the systematic study of real-world interactive decision problems. Model formulation is presented in Part I, and analysis and output interpretation in Part II. GMCR II is based upon existing and new research developments of the graph model for conflict resolution. In Part I, specially designed data structures and corresponding algorithms are implemented for generating and representing possible states, removing infeasible states, coalescing indistinguishable states, and specifying and storing allowable state transitions. Algorithms implementing different approaches to the elicitation of preferences over states enable GMCR II to construct and manage an efficient, flexible, and complete graph model of a strategic conflict.
{"title":"A decision support system for interactive decision making-Part I: model formulation","authors":"L. Fang, K. Hipel, D. Kilgour, Xiaoyong Peng","doi":"10.1109/TSMCC.2003.809361","DOIUrl":"https://doi.org/10.1109/TSMCC.2003.809361","url":null,"abstract":"A comprehensive decision support system, GMCR II, is developed for the systematic study of real-world interactive decision problems. Model formulation is presented in Part I, and analysis and output interpretation in Part II. GMCR II is based upon existing and new research developments of the graph model for conflict resolution. In Part I, specially designed data structures and corresponding algorithms are implemented for generating and representing possible states, removing infeasible states, coalescing indistinguishable states, and specifying and storing allowable state transitions. Algorithms implementing different approaches to the elicitation of preferences over states enable GMCR II to construct and manage an efficient, flexible, and complete graph model of a strategic conflict.","PeriodicalId":55005,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Re","volume":"84 1","pages":"42-55"},"PeriodicalIF":0.0,"publicationDate":"2003-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83890748","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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