Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2最新文献
{"title":"IREX: an expert system for the selection of industrial robots and its implementation in two environments","authors":"B. A. Gardone, R. Ragade","doi":"10.1145/98894.99130","DOIUrl":"https://doi.org/10.1145/98894.99130","url":null,"abstract":"This paper describes the design and implementation of a prototype robot selection expert system based on an outside/in approach. The expert system is comprised of three basic parts. The first part examines several proposed applications where automation is desired and chooses the one best suited for automation using a robot. The second part uses rules to select the configuration, drive, programming type, and playback type. The third section of the expert system examines a data base of robots and selects the best five robots for the application based on the users specifications of that job. The paper describes its implementation in KEE and the expert system's transfer to the Keystone environment on a PS-2 Model 80.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124980618","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}
{"title":"Applications of AI techniques for chip-architecture planning","authors":"Karl-Heinz Temme, Ingolf Markhof","doi":"10.1145/98894.98926","DOIUrl":"https://doi.org/10.1145/98894.98926","url":null,"abstract":"AI techniques are well suited to support the designer of digital chips during the high level synthesis step chip-architecture planning. This paper presents applications of object oriented representation, deduction rules, a truth maintenance system and justifications in this area.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740036","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}
{"title":"Airbotics: a look into the future","authors":"Pablo Gonzales","doi":"10.1145/98894.99134","DOIUrl":"https://doi.org/10.1145/98894.99134","url":null,"abstract":"What is Artificial Intelligence (AI)? Artificial Intelligence can be compared to a natural phenomena, in that, as soon as it is explained with laws of physics or mathematics it is no longer a phenomena. Since the 1950s AI has spawned new computer science fields like expert systems, intelligent assistance, speech understanding, natural language interfacing, text understanding, machine translation, computer vision, robotics, planning, knowledge acquisition, automatic programming, learning, inference, pattern matching, search, knowledge representation, and symbolic processing. These are some of the application areas for AI as listed by TI Engineering Journal, Vol. 3, Number 1. The 1980s was a decade that saw a computer revolution. What will the 1990s bring? It is a belief that the 1990s will bring the computer/robot which, in this paper, will be called Airobot. Airobot will incorporate several very important principles that most living organisms, including man, possess.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133828350","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}
{"title":"Knowledge acquisition for knowledge based process control","authors":"N. Shadbolt, R. Stobart","doi":"10.1145/98894.99139","DOIUrl":"https://doi.org/10.1145/98894.99139","url":null,"abstract":"In previous papers (Shadbolt, Robinson and Stobart 1989a, 1989b) we have described the way in which process control can benefit from the techniques and methods of knowledge based systems. In Shadbolt et al 1989a we showed how knowledge intensive methods can be incorporated in supervising and automating the control engineering procedures associated with designing, commissioning and running closed loop control. Some of the most influential current approaches to knowledge acquisition conceive of the process as a modelling activity (Morik, 1989). We can regard the use of models as a means of coping with the complexity of the development process. A model reflects, through abstraction of detail, selected characteristics of the object, device or process in the real world that it stands for.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122226434","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}
{"title":"ALEX an expert system for truck loading","authors":"R. LeMaster","doi":"10.1145/98894.98909","DOIUrl":"https://doi.org/10.1145/98894.98909","url":null,"abstract":"An expert system has been built that plans the loading of boxed products into semi-trailer trucks. The system seeks to optimize the volumetric utilization of a trailer while minimizing the likelihood of damage to the products while in transit. It is currently operating in both interactive and batch modes in the production data processing environment of a large manufacturer of household appliances. This paper describes and compares the methods of expert loaders and the expert system, as well as general information about the implementation.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125165976","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}
{"title":"Residual speech signal compression: an experiment in the practical application of neural network technology","authors":"L. Pratt, K. Cebulka, Peter Clitherow","doi":"10.1145/98894.99124","DOIUrl":"https://doi.org/10.1145/98894.99124","url":null,"abstract":"Neural networks are a popular area of research today. However, neural network algorithms have only recently proven valuable to application problems. This paper seeks to aid in the process of transferring neural network technology from research to a development environment by describing our experience in applying this technology. The application studied here is Speaker Identity Verification (SIV), which is the task of verifying a speaker's identity by comparing the speaker's voice pattern to a stored template. In this paper, we describe the application of the back-propagation neural network algorithm to one aspect of the SIV problem, called Residual Compression (RC). The RC problem is to extract useful features from a part of the speech signal that was not utilized by previous SIV systems. Here, we describe a neural network architecture, pre-processing algorithm, training methodology, and empirical results for this problem. We also present a few guidelines for the use of neural networks in applied settings.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125323928","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}
{"title":"A PC-based expert system in engineering","authors":"G. Lovegrove, Gary James Curtis, R. Farrar","doi":"10.1145/98894.98911","DOIUrl":"https://doi.org/10.1145/98894.98911","url":null,"abstract":"Over the last decade expert systems have been applied in many different domains with varying degrees of success. Much has been learned about techniques for knowledge representation, inference engines and user interfaces. Another important factor in the success of an expert system is to take into consideration at the design stage the person for whom the final system is intended: expert, informed user or beginner. Southampton University and Marchwood Laboratories of CEGB (Central Electricity Generating Board) have collaborated in recent years to produce an expert advisory system for selecting processes for welding. Apart from knowledge about the processes themselves, other factors have been taken into consideration such as equipment cost and availability, depreciation, running costs, the site, reject rate and quality level. This PC-based advisory system was designed for use by an informed but not necessarily expert welding engineer, for use in a laboratory, with an emphasis on the friendliness of the interface and flexibility of the system. Recent research work has concentrated on designing the software in an object-oriented way using an object-oriented language. This emphasis on encapsulation of data and relevant procedures has improved not only the efficiency of the system but also its overall design, meaning that future modifications or extensions can be incorporated with far greater ease. Current work includes the prototyping of tools, with the future aim of allowing a new user in a related area of engineering to use the tools to produce a similar expert system.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123824667","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}
{"title":"Recognition of semantically incorrect rules: a neural-network approach","authors":"L. Fu","doi":"10.1145/98894.99114","DOIUrl":"https://doi.org/10.1145/98894.99114","url":null,"abstract":"A novel technique that applies the neural-network learning strategy of back-propagation to recognize semantically incorrect rules is presented. When the rule strengths of most rules are semantically correct, semantically incorrect rules can be recognized if their strengths are weakened or change signs after training with correct samples. In each training cycle, the discrepancies in the belief values of goal hypotheses are propagated backward and the strengths of rules responsible for such discrepancies are modified appropriately. A function called consistent-shift is defined for measuring the shift of a rule strength in the direction consistent with the strength assigned before training and is a critical component of this technique. The viability of this technique has been demonstrated in a practical domain.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123081470","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}
{"title":"Knowledge acquisition from prescriptive texts","authors":"B. Moulin, D. Rousseau","doi":"10.1145/98894.99136","DOIUrl":"https://doi.org/10.1145/98894.99136","url":null,"abstract":"There is a growing interest for the application of artificial intelligence in law. Research activities have investigated different areas : formulating legislation with the aid of logical models, legal reasoning, case-based reasoning, developing expert systems applied to the juridical or administrative domains. In project A.C.A.T. (Acquisition des connaissances et analyse de textes), we explore the possibility of creating knowledge bases by exploiting information contained in texts which are used in organizations. Our research focuses on a particular category of prescriptive texts : regulations from the Government of Québec. In order to verify these hypothesis we are developing a knowledge-acquisition system which will enable human specialists to transform a prescriptive text into the form of a knowledge base which can be exploited by an inference engine. We introduce a model which enables us to identify three layers in prescriptive texts : the macrostructure, the microstructure and the dominial component. We describe the general architecture of the knowledge acquisition system which enables us to create “deontic” knowledge bases. We present the main knowledge structures used by the knowledge acquisition sub-system : the text grammars of macrostructure and microstructure.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116689562","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}
{"title":"Separating control from structural knowledge in construction expert systems","authors":"A. Günter, R. Cunis, Ingo Syska","doi":"10.1145/98894.98904","DOIUrl":"https://doi.org/10.1145/98894.98904","url":null,"abstract":"In most expert systems for constructional tasks the knowledge base consists of a set of facts or object definitions and a set of rules. These rules contain knowledge about correct or ideal solutions as well as knowledge on how to control the construction process. In this paper we present an approach that avoids this type of rules and thus the disadvantages caused by them. We propose a static knowledge base consisting of a set of object definitions interconnected by is-a and part-of links. This conceptual hierarchy declaratively defines a taxonomy of domain objects and the aggregation of components to composite objects. Thus, the conceptual hierarchy describes the set of all admissible solutions to a constructional problem. Interdependencies between objects are represented by constraints. A solution is a syntactically complete and correct partial instantiation of the conceptual hierarchy. No control knowledge is included in the conceptual hierarchy. Instead, the control mechanism will use it as a guideline. It is thus possible to determine in which respects a current partial solution is incomplete, simply by comparing it with the conceptual hierarchy syntactically. The most important advantage of this approach is the ability to represent control knowledge and structural knowledge separately.","PeriodicalId":175812,"journal":{"name":"Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126319549","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}