A description is given of a knowledge base design and prototyping tool, Crayon, based on an enhanced formal functional data model implemented in Prolog. The objective was to explore use of this data model for knowledge base management. A discussion is presented of the advantages of the model (formal representation, semantic richness and simplicity) from the perspective of two knowledge representation guidelines and the advantages of using Prolog as the implementation language for knowledge base prototyping. The authors propose and discuss theoretical enhancements to the functional data model in the form of knowledge-oriented constraints.<>
{"title":"A knowledge-base design and application prototyping tool based on an enhanced functional data model","authors":"S. Prabhakar, S. Navathe","doi":"10.1109/TAI.1991.167076","DOIUrl":"https://doi.org/10.1109/TAI.1991.167076","url":null,"abstract":"A description is given of a knowledge base design and prototyping tool, Crayon, based on an enhanced formal functional data model implemented in Prolog. The objective was to explore use of this data model for knowledge base management. A discussion is presented of the advantages of the model (formal representation, semantic richness and simplicity) from the perspective of two knowledge representation guidelines and the advantages of using Prolog as the implementation language for knowledge base prototyping. The authors propose and discuss theoretical enhancements to the functional data model in the form of knowledge-oriented constraints.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"6 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":"115416137","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 optimal arc consistency algorithm AC-4 was given by R. Mohr and T.C. Henderson (1986). AC-4 has costO(ea/sup 2/), and cost(na/sup 2/) for scene labeling. Although their algorithm is indeed optimal, under certain conditions a constraint satisfaction problem can be transformed into a less complex problem. Conditions and mechanisms are presented for such transformations, and it is shown how to factor relations into more manageable components. A description is given of how factorization can reduce AC-4's cost to O(ea), and this result is applied to RETE match.<>
R. Mohr和T.C. Henderson(1986)给出了最优弧一致性算法AC-4。AC-4有cost(ea/sup 2/)和cost(na/sup 2/)用于场景标注。虽然他们的算法确实是最优的，但在一定条件下，约束满足问题可以转化为不那么复杂的问题。介绍了这种转换的条件和机制，并展示了如何将关系分解为更易于管理的组件。描述了因式分解如何将AC-4的成本降低到0 (ea)，并将此结果应用于RETE匹配。
{"title":"Arc consistency for factorable relations","authors":"M. Perlin","doi":"10.1109/TAI.1991.167113","DOIUrl":"https://doi.org/10.1109/TAI.1991.167113","url":null,"abstract":"An optimal arc consistency algorithm AC-4 was given by R. Mohr and T.C. Henderson (1986). AC-4 has costO(ea/sup 2/), and cost(na/sup 2/) for scene labeling. Although their algorithm is indeed optimal, under certain conditions a constraint satisfaction problem can be transformed into a less complex problem. Conditions and mechanisms are presented for such transformations, and it is shown how to factor relations into more manageable components. A description is given of how factorization can reduce AC-4's cost to O(ea), and this result is applied to RETE match.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"39 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":"115418902","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 is presented for constructive induction, in which new attributes are constructed as various functions of original attributes. Such a method is called data-driven constructive induction, because new attributes are derived from an analysis of the data (examples) rather than the generated rules. Attribute construction and rule generation are repeated until a termination condition, such as the satisfaction of a rule quality measure, is met. The first step of this method, the generation of new attributes, has been implemented in AQ17-PRE. Initial experiments with AQ17-PRE have shown that it leads to an improvement of the learned rules in terms of both their simplicity and their accuracy on testing examples.<>
{"title":"Data-driven constructive induction in AQ17-PRE: A method and experiments","authors":"E. Bloedorn, R. Michalski","doi":"10.1109/TAI.1991.167073","DOIUrl":"https://doi.org/10.1109/TAI.1991.167073","url":null,"abstract":"A method is presented for constructive induction, in which new attributes are constructed as various functions of original attributes. Such a method is called data-driven constructive induction, because new attributes are derived from an analysis of the data (examples) rather than the generated rules. Attribute construction and rule generation are repeated until a termination condition, such as the satisfaction of a rule quality measure, is met. The first step of this method, the generation of new attributes, has been implemented in AQ17-PRE. Initial experiments with AQ17-PRE have shown that it leads to an improvement of the learned rules in terms of both their simplicity and their accuracy on testing examples.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"105 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":"127532538","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 efficient algorithm to search for a minimal finite state automaton (FSA) is presented. This algorithm eliminates all the redundant states in a given FSA and is guaranteed to produce an optimal solution for a reduced FSA. The performance is achieved because of the application of a fail-first heuristics in search tree level and nodal ordering and taking advantage of an efficient search space pruning criterion in search tree generation and in the search process.<>
{"title":"Searching for a minimal finite state automaton (FSA)","authors":"R. Puri, J. Gu","doi":"10.1109/TAI.1991.167123","DOIUrl":"https://doi.org/10.1109/TAI.1991.167123","url":null,"abstract":"An efficient algorithm to search for a minimal finite state automaton (FSA) is presented. This algorithm eliminates all the redundant states in a given FSA and is guaranteed to produce an optimal solution for a reduced FSA. The performance is achieved because of the application of a fail-first heuristics in search tree level and nodal ordering and taking advantage of an efficient search space pruning criterion in search tree generation and in the search process.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"15 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":"125310699","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 author presents an actor language, GMAL (Gosseyn machine actor language), a tool for knowledge representation based on a reflective representation of the actor model. This modelization provides interesting features such as modularity, flexibility, inherent parallelism, and easy integration of intelligent functions (introspection).<>
{"title":"GMAL: a tool for AI systems construction","authors":"S. Hassas","doi":"10.1109/TAI.1991.167047","DOIUrl":"https://doi.org/10.1109/TAI.1991.167047","url":null,"abstract":"The author presents an actor language, GMAL (Gosseyn machine actor language), a tool for knowledge representation based on a reflective representation of the actor model. This modelization provides interesting features such as modularity, flexibility, inherent parallelism, and easy integration of intelligent functions (introspection).<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"10 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":"115037478","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}
Hardware implementations and single-instruction-stream/multiple-data-stream (SIMD) simulations are relatively inflexible, while multiple-instruction-stream (MIMD) simulations often trade their flexibility for increased efficiency. An alternative technique is presented which is based on pipelining fewer but larger messages through parallel, broadcast/accumulate trees. This method exploits both the structural parallelism of neural networks and the data parallelism of neural algorithms. The mapping is flexible to changes in the network architecture and learning algorithm and is suited to a variety of computer configurations. Experimental results show a higher efficiency than similar implementation.<>
{"title":"MIMD implementation of neural networks through pipelined, parallel communication trees","authors":"P. Wohl, T. Christopher","doi":"10.1109/TAI.1991.167079","DOIUrl":"https://doi.org/10.1109/TAI.1991.167079","url":null,"abstract":"Hardware implementations and single-instruction-stream/multiple-data-stream (SIMD) simulations are relatively inflexible, while multiple-instruction-stream (MIMD) simulations often trade their flexibility for increased efficiency. An alternative technique is presented which is based on pipelining fewer but larger messages through parallel, broadcast/accumulate trees. This method exploits both the structural parallelism of neural networks and the data parallelism of neural algorithms. The mapping is flexible to changes in the network architecture and learning algorithm and is suited to a variety of computer configurations. Experimental results show a higher efficiency than similar implementation.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"52 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":"128295460","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 feature based stereo matching system is designed. A hierarchical grouping process that groups line segments into more complex structures that are easier to match is proposed. The hierarchy consists of lines, vertices, edges and surfaces. Matching starts at the highest level of the hierarchy (surfaces) and proceeds to the lowest (lines). Higher level features are easier to match, because they are fewer in number and more distinct in form. These matches then constrain the matches at lower levels. Perceptual and structural relations are used to group matches into islands of certainty. A truth maintenance system (TMS) is used to enforce grouping constraints and eliminates inconsistent match groupings.<>
{"title":"Hierarchical stereo matching using feature groupings","authors":"V. Venkateswar, R. Chellappa","doi":"10.1109/TAI.1991.167100","DOIUrl":"https://doi.org/10.1109/TAI.1991.167100","url":null,"abstract":"A feature based stereo matching system is designed. A hierarchical grouping process that groups line segments into more complex structures that are easier to match is proposed. The hierarchy consists of lines, vertices, edges and surfaces. Matching starts at the highest level of the hierarchy (surfaces) and proceeds to the lowest (lines). Higher level features are easier to match, because they are fewer in number and more distinct in form. These matches then constrain the matches at lower levels. Perceptual and structural relations are used to group matches into islands of certainty. A truth maintenance system (TMS) is used to enforce grouping constraints and eliminates inconsistent match groupings.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"9 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":"126803385","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 incremental algorithm for updating the Galois lattice is proposed where new objects may be dynamically added by modifying the existing lattice. A large experimental application reveals that adding a new object may be done in time proportional to the number of objects on the average. When there is a fixed upper bound on the number of properties related to an object, which is the case in practical applications, the worst case analysis of the algorithm confirms the experimental observations of linear growth with respect to the number of objects. Algorithms for generating rules from the lattice are also given.<>
{"title":"Learning algorithms using a Galois lattice structure","authors":"R. Godin, R. Missaoui, Hassan Alaoui","doi":"10.1109/TAI.1991.167072","DOIUrl":"https://doi.org/10.1109/TAI.1991.167072","url":null,"abstract":"An incremental algorithm for updating the Galois lattice is proposed where new objects may be dynamically added by modifying the existing lattice. A large experimental application reveals that adding a new object may be done in time proportional to the number of objects on the average. When there is a fixed upper bound on the number of properties related to an object, which is the case in practical applications, the worst case analysis of the algorithm confirms the experimental observations of linear growth with respect to the number of objects. Algorithms for generating rules from the lattice are also given.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"2 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":"134090528","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 axiomatization of STA (systolic temporal arithmetic) defines rules for the systolic array in the language of the predicate calculus. The STA formalism is briefly reviewed and an automated verifier is constructed using Prolog. The verification tool is developed to produce a sound and efficient verification process and to provide short-cuts to justify systolic array designs. The STA specifications and the corresponding Prolog programs can be written using an almost identical notation.<>
{"title":"Verification tool for systolic array design","authors":"F. Lin, T. Shih, N. Ling","doi":"10.1109/TAI.1991.167030","DOIUrl":"https://doi.org/10.1109/TAI.1991.167030","url":null,"abstract":"The axiomatization of STA (systolic temporal arithmetic) defines rules for the systolic array in the language of the predicate calculus. The STA formalism is briefly reviewed and an automated verifier is constructed using Prolog. The verification tool is developed to produce a sound and efficient verification process and to provide short-cuts to justify systolic array designs. The STA specifications and the corresponding Prolog programs can be written using an almost identical notation.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"68 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":"131845869","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 assembly planning system is presented that operates based on a recursive decomposition of an assembly into subassemblies, and uses design for assembly (DFA) analysis to guide the generation of a preferred assembly plan. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. The system handles nonreversible as well as reversible assembly tasks through backward assembly planning.<>
{"title":"Backward assembly planning","authors":"Sukhan Lee","doi":"10.1109/TAI.1991.167122","DOIUrl":"https://doi.org/10.1109/TAI.1991.167122","url":null,"abstract":"An assembly planning system is presented that operates based on a recursive decomposition of an assembly into subassemblies, and uses design for assembly (DFA) analysis to guide the generation of a preferred assembly plan. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. The system handles nonreversible as well as reversible assembly tasks through backward assembly planning.<<ETX>>","PeriodicalId":371778,"journal":{"name":"[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91","volume":"22 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":"114480173","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：