An enumerative approach for selective generation of prime implicants of a theory in conjunctive normal form is presented. The method is based on 0-1 programming. Optimal solutions of the integer linear program associated with the theory correspond to prime implicants. All prime implicants can be obtained by augmenting the integer program with new constraints which discard the already obtained solutions. The method allows to implement preference criteria in the choice of the prime implicants to find.
{"title":"Computing prime implicants by integer programming","authors":"C. Pizzuti","doi":"10.1109/TAI.1996.560473","DOIUrl":"https://doi.org/10.1109/TAI.1996.560473","url":null,"abstract":"An enumerative approach for selective generation of prime implicants of a theory in conjunctive normal form is presented. The method is based on 0-1 programming. Optimal solutions of the integer linear program associated with the theory correspond to prime implicants. All prime implicants can be obtained by augmenting the integer program with new constraints which discard the already obtained solutions. The method allows to implement preference criteria in the choice of the prime implicants to find.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130589502","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 paper introduces ADHOC, a tool that integrates statistical methods and machine learning techniques to perform effective feature selection. Feature selection plays a central role in the data analysis process since redundant and irrelevant features often degrade the performance of induction algorithms, both in speed and predictive accuracy. ADHOC combines the advantages of both filter and feedback approaches to feature selection to enhance the understanding of the given data and increase the efficiency of the feature selection process. We report results of extensive experiments on real world data which demonstrate the effectiveness of ADHOC as data reduction technique as well as feature selection method. ADHOC has been employed in the analysis of several corporate databases. In particular, it is currently used to support the difficult task of early estimation of the cost of software projects.
{"title":"ADHOC: a tool for performing effective feature selection","authors":"M. Richeldi, P. Lanzi","doi":"10.1109/TAI.1996.560434","DOIUrl":"https://doi.org/10.1109/TAI.1996.560434","url":null,"abstract":"The paper introduces ADHOC, a tool that integrates statistical methods and machine learning techniques to perform effective feature selection. Feature selection plays a central role in the data analysis process since redundant and irrelevant features often degrade the performance of induction algorithms, both in speed and predictive accuracy. ADHOC combines the advantages of both filter and feedback approaches to feature selection to enhance the understanding of the given data and increase the efficiency of the feature selection process. We report results of extensive experiments on real world data which demonstrate the effectiveness of ADHOC as data reduction technique as well as feature selection method. ADHOC has been employed in the analysis of several corporate databases. In particular, it is currently used to support the difficult task of early estimation of the cost of software projects.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116652158","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. Vlassis, N. Sgouros, G. Efthivoulidis, G. Papakonstantinou, P. Tsanakas
We describe a novel global path planning method for autonomous qualitative navigation in indoor environments. Global path planning operates on top of a qualitative map of the environment that describes variations in sensor behavior between adjacent regions in space. The method takes into consideration the global topology of the environment and applies a set of criteria that can minimize the errors in the navigational accuracy of a robotic wheelchair. Our approach uses a modified version of the Dijkstra's shortest path algorithm that takes into consideration the curvature of the trajectory and the off-wall distance of the map points. The algorithm computes in real-time a set of optimal paths for reaching the destination. We have tested our global path planning method in simulation in representative indoor environments with above average complexity. Based on these experiments we have determined empirically a set of values for the parameters of the algorithm that almost always lead to the selection of optimal paths in these environments.
{"title":"Global path planning for autonomous qualitative navigation","authors":"N. Vlassis, N. Sgouros, G. Efthivoulidis, G. Papakonstantinou, P. Tsanakas","doi":"10.1109/TAI.1996.560476","DOIUrl":"https://doi.org/10.1109/TAI.1996.560476","url":null,"abstract":"We describe a novel global path planning method for autonomous qualitative navigation in indoor environments. Global path planning operates on top of a qualitative map of the environment that describes variations in sensor behavior between adjacent regions in space. The method takes into consideration the global topology of the environment and applies a set of criteria that can minimize the errors in the navigational accuracy of a robotic wheelchair. Our approach uses a modified version of the Dijkstra's shortest path algorithm that takes into consideration the curvature of the trajectory and the off-wall distance of the map points. The algorithm computes in real-time a set of optimal paths for reaching the destination. We have tested our global path planning method in simulation in representative indoor environments with above average complexity. Based on these experiments we have determined empirically a set of values for the parameters of the algorithm that almost always lead to the selection of optimal paths in these environments.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114990654","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}
Classification involves associating instances with particular classes by maximizing intra-class similarities and minimizing inter-class similarities. The paper presents a novel approach to case-based classification. The algorithm is based on a notion of similarity assessment and was developed for supporting flexible retrieval of relevant information. Validity of the proposed approach is tested on real world domains, and the system's performance is compared to that of other machine learning algorithms.
{"title":"Case-based classification using similarity-based retrieval","authors":"I. Jurisica, J. Glasgow","doi":"10.1109/TAI.1996.560735","DOIUrl":"https://doi.org/10.1109/TAI.1996.560735","url":null,"abstract":"Classification involves associating instances with particular classes by maximizing intra-class similarities and minimizing inter-class similarities. The paper presents a novel approach to case-based classification. The algorithm is based on a notion of similarity assessment and was developed for supporting flexible retrieval of relevant information. Validity of the proposed approach is tested on real world domains, and the system's performance is compared to that of other machine learning algorithms.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129603223","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}
Data mining algorithms including machine learning, statistical analysis, and pattern recognition techniques can greatly improve our understanding of data warehouses that are now becoming more widespread. In this paper, we focus on classification algorithms and review the need for multiple classification algorithms. We describe a system called /spl Mscr//spl Lscr//spl Cscr/++ which was designed to help choose the appropriate classification algorithm for a given dataset by making it easy to compare the utility of different algorithms on a specific dataset of interest. /spl Mscr//spl Lscr//spl Cscr/++ not only provides a work-bench for such comparisons, but also provides a library of C++ classes to aid in the development of new algorithms, especially hybrid algorithms and multi-strategy algorithms. Such algorithms are generally hard to code from scratch. We discuss design issues, interfaces to other programs, and visualization of the resulting classifiers.
{"title":"Data mining using /spl Mscr//spl Lscr//spl Cscr/++ a machine learning library in C++","authors":"Ron Kohavi, D. Sommerfield, James Dougherty","doi":"10.1109/TAI.1996.560457","DOIUrl":"https://doi.org/10.1109/TAI.1996.560457","url":null,"abstract":"Data mining algorithms including machine learning, statistical analysis, and pattern recognition techniques can greatly improve our understanding of data warehouses that are now becoming more widespread. In this paper, we focus on classification algorithms and review the need for multiple classification algorithms. We describe a system called /spl Mscr//spl Lscr//spl Cscr/++ which was designed to help choose the appropriate classification algorithm for a given dataset by making it easy to compare the utility of different algorithms on a specific dataset of interest. /spl Mscr//spl Lscr//spl Cscr/++ not only provides a work-bench for such comparisons, but also provides a library of C++ classes to aid in the development of new algorithms, especially hybrid algorithms and multi-strategy algorithms. Such algorithms are generally hard to code from scratch. We discuss design issues, interfaces to other programs, and visualization of the resulting classifiers.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121853697","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 paper presents a language for the development of multi agent systems that allows a user to write programs with a small effort thanks to a predefined agent model and a set of specialized primitives for agent management. Moreover the user can develop agent parts at a low level, taking advantage of all the potentialities of C++, Common Lisp and Java object oriented languages, and reusing a large part of the C, C++, Lisp, Common Lisp and Java software available on the Internet.
{"title":"Integrating agents and objects to develop distributed AI systems","authors":"A. Poggi","doi":"10.1109/TAI.1996.560775","DOIUrl":"https://doi.org/10.1109/TAI.1996.560775","url":null,"abstract":"The paper presents a language for the development of multi agent systems that allows a user to write programs with a small effort thanks to a predefined agent model and a set of specialized primitives for agent management. Moreover the user can develop agent parts at a low level, taking advantage of all the potentialities of C++, Common Lisp and Java object oriented languages, and reusing a large part of the C, C++, Lisp, Common Lisp and Java software available on the Internet.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117239644","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}
S. Michos, E. Stamatatos, N. Fakotakis, G. Kokkinakis
The presented work is strongly motivated by the need for categorizing unrestricted text in terms of a functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, a three level description of FS is given that comprises: (a) the basic categories of FS; (b) the main features that characterize each one of the above categories; and (c) the linguistic identifiers that act as style markers in text for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings, as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real world text, and recognition of style shift between adjacent portions of text.
{"title":"An empirical text categorizing computational model based on stylistic aspects","authors":"S. Michos, E. Stamatatos, N. Fakotakis, G. Kokkinakis","doi":"10.1109/TAI.1996.560403","DOIUrl":"https://doi.org/10.1109/TAI.1996.560403","url":null,"abstract":"The presented work is strongly motivated by the need for categorizing unrestricted text in terms of a functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, a three level description of FS is given that comprises: (a) the basic categories of FS; (b) the main features that characterize each one of the above categories; and (c) the linguistic identifiers that act as style markers in text for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings, as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real world text, and recognition of style shift between adjacent portions of text.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124443195","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}
Presents the design of an interactive tool for minimal updates of views in knowledge bases, while maintaining the consistency, expressed by a set of integrity constraints. Minimality is based on a partial order which captures the distance between the old state, before the update request, and the new state, in which the request is satisfied. On the user interface part, once the schema and the database are selected from the initial menu, the system automatically generates the selection menus and communication boxes to guide the user through the update.
{"title":"Meta Updater: an interactive tool for minimal view updates in knowledge bases","authors":"Goce Trajcevski, Jorge Lobo, N. Grover","doi":"10.1109/TAI.1996.560794","DOIUrl":"https://doi.org/10.1109/TAI.1996.560794","url":null,"abstract":"Presents the design of an interactive tool for minimal updates of views in knowledge bases, while maintaining the consistency, expressed by a set of integrity constraints. Minimality is based on a partial order which captures the distance between the old state, before the update request, and the new state, in which the request is satisfied. On the user interface part, once the schema and the database are selected from the initial menu, the system automatically generates the selection menus and communication boxes to guide the user through the update.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"89 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133719405","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 autonomous system uses sensors in order to update an uncertain representation of its environment, which must remain well-grounded with regards to the risks and the constraints of its mission. The choice of a framework for the representation of beliefs which is adapted to deal with both time and uncertainty is a crucial point. A perception strategy should be founded on an evaluation of the relevance of the beliefs of the system in order to collect the most useful information at the most opportune time. This paper addresses the problem of taking time and ignorance into account in the representation of the uncertain beliefs of the system about the world. The paper proposes a well-adapted approach to the design of a perception strategy for an autonomous surveillance system in a changing environment together with initial results of simulations.
{"title":"Strategy of perception and temporal representation of beliefs","authors":"P. Fabiani","doi":"10.1109/TAI.1996.560399","DOIUrl":"https://doi.org/10.1109/TAI.1996.560399","url":null,"abstract":"An autonomous system uses sensors in order to update an uncertain representation of its environment, which must remain well-grounded with regards to the risks and the constraints of its mission. The choice of a framework for the representation of beliefs which is adapted to deal with both time and uncertainty is a crucial point. A perception strategy should be founded on an evaluation of the relevance of the beliefs of the system in order to collect the most useful information at the most opportune time. This paper addresses the problem of taking time and ignorance into account in the representation of the uncertain beliefs of the system about the world. The paper proposes a well-adapted approach to the design of a perception strategy for an autonomous surveillance system in a changing environment together with initial results of simulations.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116468928","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}
We discuss the interesting perspective offered by the Coulomb Energy network and we identify certain disadvantages with the existing approach to training it. We address these problems by constraining its architecture (topology) and offer a derivation of the new associated training algorithm. We study further refinements of this algorithm. Most notably, existing genetic algorithms are employed as initial search techniques and simulation results are provided.
{"title":"Refinements in training schemes for the Coulomb Energy network","authors":"John F. Vassilopoulos, C. Koutsougeras","doi":"10.1109/TAI.1996.560451","DOIUrl":"https://doi.org/10.1109/TAI.1996.560451","url":null,"abstract":"We discuss the interesting perspective offered by the Coulomb Energy network and we identify certain disadvantages with the existing approach to training it. We address these problems by constraining its architecture (topology) and offer a derivation of the new associated training algorithm. We study further refinements of this algorithm. Most notably, existing genetic algorithms are employed as initial search techniques and simulation results are provided.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124601891","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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