{"title":"Knowledge engineering problems during expert system development","authors":"Douglas Chubb","doi":"10.1145/1102872.1102873","DOIUrl":"https://doi.org/10.1145/1102872.1102873","url":null,"abstract":"Expert systems are artificial intelligence computer programs which emulate human expertise within some domain of interest. The recent financial successes of such expert systems as PROSPECTOR and XCON have created a demand in government and industry for the developmental skills necessary to build such systems. Expert system knowledge engineering and in particular knowledge acquisition continues to be the most difficult process encountered during expert system develpment. Reasons for knowledge acquisition difficulties find their basis in philosophical assumptions made about the cognitive process. The assumptions are that human cognition consists of discrete elements which may be characterized (by some introspection) to produce an expert system rule; secondly, that the processing requirements for expert domain heuristics is equivalent to the processing requirements for a deterministic rule set. Suggestions for improving the knowledge engineering process are offered.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116756805","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":"The discrete event simulation computer - DESC","authors":"Meir Barel","doi":"10.1145/1103235.1103237","DOIUrl":"https://doi.org/10.1145/1103235.1103237","url":null,"abstract":"Simulation of large models on digital computers is often limited by the high computational expenses. The Discrete Event Simulation Computer (DESC) reported here improves simulation performance through an exploitation of parallelism inherent in simulation, with regard to list processing, random number generation, statistical analysis and program control. The DESC consists of a set of nodes that communicate via FIFO-buffered channels (i.e. do not share memory among nodes). In order to achieve high system throughput dedicated hardware modules were developed; this includes new concepts for a list processor and a hardware random number generator for uniform deviates.The implementation of simulation languages such as SIMULA, SIMSCRIPT or GPSS is conceptually straightforward. We chose SIMULA as the frame language concept. Metrics applicable to simulation throughput and simulation costs are defined and compared with the CD CYBER 175.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126804886","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 high speed list processor for discrete event multiprocessor: simulators","authors":"Meir Barel","doi":"10.1145/1102581.1102583","DOIUrl":"https://doi.org/10.1145/1102581.1102583","url":null,"abstract":"List processing plays a central role in simulation programs. It is apparent that a distributed list processing is essential for a distributed simulation. The list processor reported here is a special microprogrammed processor, according to the co-processor concept, whose architecture 1) is optimized for the execution of list and arithmetic operations, and 2) support distributed list processing on several list processors. In order to accommodate a wide range of list applications a comprehensive basic instruction set has been implemented which allows the execution of many desired list operations, e.g. complex searching and sorting algorithms. For a specific application (e.g. event list manipulation) a high level instruction set can be built by using these basic instructions. For attribute manipulation an arithmetic instruction set (floating point) is also included.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"107 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1983-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114002258","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":"General approach to formulation and solution of simulation models","authors":"S. Iyengar","doi":"10.1145/1102850.1102857","DOIUrl":"https://doi.org/10.1145/1102850.1102857","url":null,"abstract":"This paper will report on a general approach to the formulation and solution to simulation models.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131304876","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":"Small-sample behavior of Weighted Least Squares in experimental design applications","authors":"J. Kleijnen, Renée Brent, Rien Brouwers","doi":"10.1145/1102850.1102853","DOIUrl":"https://doi.org/10.1145/1102850.1102853","url":null,"abstract":"In experimental design applications unbiased estimators s<sup>2</sup><inf>i</inf> of the variances σ<sup>2</sup><inf>i</inf> are possible. These estimators may be used in Weighted Least Squares (WLS) when estimating the parameters β The resulting small-sample behavior is investigated in a Monte Carlo experiment. This experiment shows that an asymptotically valid covariance formula can be used if s<sup>2</sup><inf>i</inf> is based on, say, at least 5 observations. The WLS estimator based on estimators s<sup>2</sup><inf>i</inf> gives more accurate estimators of β, provided the σ<sup>2</sup><inf>i</inf> differ by a factor, say, 10.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129379815","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":"Patterns of modelling: towards a conceptual basis for discrete event simulation","authors":"W. Kreutzer","doi":"10.1145/1102850.1102851","DOIUrl":"https://doi.org/10.1145/1102850.1102851","url":null,"abstract":"Success of any standardization effort is highly sensitive to user acceptance and satisfaction. Conceptual simplicity, congruence, power, transparency, flexibility and interpretative efficiency of modelling methodologies and their processor systems are at least partially conflicting goals between which suitable tradeoffs have to be made.Solutions to this problem will neither be found through excessive generality nor a proliferation of weakly related special purpose concepts, but by a reliable approach towards engineering of complex systems relative to a secure and powerfull conceptual basis.This paper argues in favour of spectra of high-level, user-oriented modelling interfaces built on top of a hierarchically extended base language. A brief outline of cognitive structures in problem solving and discrete event simulation serves to support the subsequent discussion of basic conceptual and notational abstractions and their mapping into implementation structures.Some final remarks on costs and benefits of instrumental congruences and the impact of technological developments on price/performance tradeoffs between information processing system components serve to underline the recommendations.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115501115","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":"Some problems in the design of combined languages","authors":"J. Barnden","doi":"10.1145/1102850.1102856","DOIUrl":"https://doi.org/10.1145/1102850.1102856","url":null,"abstract":"The purpose of this article is to air some problems and issues I have encountered on trying to derive principles for the design of combined continuous-discrete simulation languages for digital computers [1, 2, 3, 4, 5]. The presentation is intended to provoke discussion rather than to provide definitive analysis. I am especially conerned with: interaction between parallel' components; discontinutuity and the discrete/continuous dichotomy; and state-events.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121029789","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":"The situation is this ....","authors":"R. Ellinger","doi":"10.1145/1102850.1102855","DOIUrl":"https://doi.org/10.1145/1102850.1102855","url":null,"abstract":"One normally accepted taxonomy classifies simulations into continuous, discrete, and hybrid. But this taxonomy fails to note a significant division of simulations, particularly for the purposes of instruction and personnel training. Most business and research simulations--and many instructional simulations--are of the <u>laboratory</u> type (see figure 1). The simulation operator sets up the operating conditions--i.e. the values of the independent variables and parameters that define the initial state--then allows the computer model to run. This model is usually a set of mathematical functions that are sequenced by an algorithm and may contain one or more stochastic variables. This is the type of simulation subdivided in the taxonomy.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121882106","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":"Cost effectiveness of the simulation languages: GPSS 1100 and SIMULA I","authors":"J. Niedereichholz","doi":"10.1145/1102850.1102859","DOIUrl":"https://doi.org/10.1145/1102850.1102859","url":null,"abstract":"Comparative GPSS 1100 and SIMULA I measurements using a simple job shop simulation.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116614372","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":"Conversion of long integers from one base to another under size constraints","authors":"T. A. Kovats","doi":"10.1145/1102850.1102852","DOIUrl":"https://doi.org/10.1145/1102850.1102852","url":null,"abstract":"A long integer is a vector whose elements are the digits of a number represented in a number system based on a given base; this construct is useful in extended-precision calculations. A routine is presented for converting a long integer froe one base to another, as well as routines for doing addition and multiplication of long integers.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131515960","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}