A general approach to implement propagation and simplification of constraints consists of applying rules over these constraints. However, a difficulty that arises frequently when writing a constraint solver is to dete...
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A general approach to implement propagation and simplification of constraints consists of applying rules over these constraints. However, a difficulty that arises frequently when writing a constraint solver is to determine the constraint propagation algorithm. In previous work, different methods for automatic generation of rule-based solvers for constraints defined over finite domains have been proposed 1,2,3,4 . In this paper, we present a method for generating rule-based solvers for constraint predicates defined by means of a constraint logic program, even when the constraint domain is infinite.
The effort required for the initial drafting of a plan is often a real barrier to developing a useful and high quality schedule for a construction project. The goal of this paper is to demonstrate how an expert system...
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The effort required for the initial drafting of a plan is often a real barrier to developing a useful and high quality schedule for a construction project. The goal of this paper is to demonstrate how an expert system with an editable rule base can be combined with standard templates of modifiable, predefined knowledge within a project management system in order to generate draft schedules based on limited user input. The user can capitalize on past experience by creating a template for each recurring project type. The knowledge contained in the templates is broken down into a physical view (i.e., what is being built), a process view (i.e., how it will be built), and rules for scaling the templates and computing durations based on user input. The physical view is a hierarchical breakdown structure of components that describes (without quantifying) the physical and spatial characteristics of the project type. The process view contains a list of typical activities and the logic relationships that describe their sequencing. The rules serve to link and then expand the two views in order to generate a draft schedule for the project-at-hand once its scale is specified. The feasibility and capabilities of the proposed approach are demonstrated in the context of a full-sized project composed of three buildings.
Knowledge objects are an integration of the object-oriented paradigm with logic rules. The proper integration provides a flexible and powerful environment, as rule-based components provide facilities for deductive ret...
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Knowledge objects are an integration of the object-oriented paradigm with logic rules. The proper integration provides a flexible and powerful environment, as rule-based components provide facilities for deductive retrieval and pattern matching, and object-oriented components provide a clear intuitive structure for programs in the form of class hierarchies. based on the knowledge object concept, this paper presents a factor-centered representation language, Factor++, which models logic rules into the object-oriented paradigm, and a scheduling system, Schedular, using the Eactor++ framework. The construction of Schedular demonstrates that by using an object-oriented representation of knowledge objects, users can be given explicit control of the object hierarchy to customize the system to their particular needs, which includes letting users select among scheduling and other methods. In Schedular, rules are designed as derivation rules and constraint rules. The purpose of rules is either to restrict object structure and behavior, or to infer new data from the existing data. rules are arranged in positions so that object methods are automatically firing up if environment changes are detected by these rules.
Research and development in Information Technology is increasingly turning to techniques popular in social science fields for the design, testing and validation of new systems. Case studies, in particular, are used as...
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Research and development in Information Technology is increasingly turning to techniques popular in social science fields for the design, testing and validation of new systems. Case studies, in particular, are used as a powerful technique in all areas of system development and research. Manufacturing Planning and Control (MPC) systems are typical of such systems where the problems are no longer predominantly technical. One of the main barriers to the implementation of successful MPC systems is accurate identification of the true user requirements. This paper describes the use of multiple case studies for the development of a rule-based system for the specification of suitable MPC systems in manufacturing companies. The case studies are carried out in an iterative manner to enable the rule-base to be updated and re-tested with each successive cycle. The use of multiple case-study research cycles enables the accuracy and usability of the rule-base to be assessed as the research progresses. The rule-base comprises inputs (company characteristics and management concerns), rules (structured around reasoning) and outputs (recommended MPC system activities). It is shown that it can be expected to be greater than 90% accurate for any small to medium sized enterprise (SME) engaged in batch manufacturing.
This paper describes CAPE, a programming environment combining CLIPS And Perl with Extensions. CLIPS is an efficient and expressive forward-chaining rule-based system with a flexible object system. Perl is a popular p...
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This paper describes CAPE, a programming environment combining CLIPS And Perl with Extensions. CLIPS is an efficient and expressive forward-chaining rule-based system with a flexible object system. Perl is a popular procedural language with extremely powerful regular expression matching facilities, and a huge library of freely available software. CAPE closely integrates these languages, and provides extensions to facilitate building systems with an intimate mixture of the two. The paper describes the facilities CAPE offers programmers and the demonstration systems and "component applications" distributed with it. The use of the system is then discussed with reference to DIME (Distributed Information Manipulation Environment), a toolkit being developed to support identifying and coordinating the use of external knowledge sources. Finally, planned developments of the system are indicated. (C) 2000 Elsevier Science B.V. All rights reserved.
This paper presents a new architecture for simulating virtual humans in complex urban environments. The approach is based on the integration of six modules. Four key modules are used in older to manage environmental d...
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This paper presents a new architecture for simulating virtual humans in complex urban environments. The approach is based on the integration of six modules. Four key modules are used in older to manage environmental data, simulate human crowds, control intel actions between virtual humans and objects, and generate tasks based on a rule-based behavior al model. The communication between these modules is made through a client/server system. Finally, all low-level virtual human actions are delegated to a single motion and behavioral control module. Our architecture combines various human and object simulation aspects, based on the coherent extraction and classification of information from a virtual city database. This architecture is discussed in this paper, together with a detailed case study example.
rule-based expert system shells have one important drawback in handling uncertain knowledge. It is the drawback that the style of their fuzzy reasoning process and their semantics both are not compatible with those of...
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rule-based expert system shells have one important drawback in handling uncertain knowledge. It is the drawback that the style of their fuzzy reasoning process and their semantics both are not compatible with those of relational databases. On the other hand, production rule-based languages whose structure is similar to that of the databases fail to possess the fuzzy reasoning ability. Proposed in this paper is a framework to support a semantic based inexact match with Fuzzy Match Predicate (F_MP). In a uniform way it allows matches including fuzzy linguistic variables as well as fuzzy numbers. Our framework also adopts a design alternative to conform not only the semantics of its knowledge representation but also its reasoning style to those of the relational framework. It is a natural consequence that such a design alternative entails a seamless integration of our work into the relational databases. A major advantage of our framework is that it can be implemented on top of the production rule-based languages without modifying their discrimination networks. That is mainly due to the minimal semantic gap between the framework and the languages. In this paper, we demonstrate that: (1) F_MP is a uniform framework to provide the rule-based languages with fuzzy match facilities semantically enhanced, and that (2) its semantic conform well to that of the relational one. We also develop a rule-evaluation mechanism well suited to the aims.
This paper is a report of ongoing research on the computational modeling of beat induction which aims at achieving a better understanding of the perceptual processes involved by ordering and reformulating existing mod...
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This paper is a report of ongoing research on the computational modeling of beat induction which aims at achieving a better understanding of the perceptual processes involved by ordering and reformulating existing models. One family of rule-based beat induction models is described (Longuet-Higgins and Lee, 1982;Lee, 1985;Longuet-Higgins, 1994), along with the presentation of analysis methods that allow an evaluation of the models in terms of their in- and output spaces, abstracting from internal detail. It builds on work described in (Desain and Honing, 1994b). The present paper elaborates these methods and presents the results obtained. It will be shown that they can be used to characterize the differences between these models, a point that was difficult to assess previously Furthermore, the first results of using the method to improve the existing rule-based models are presented, by describing the most effective version of a specific rule, and the most effective parameter settings.
We present the architecture and a performance assessment of an extensible query optimizer written in Venus. Venus is a general-purpose active-database rule language embedded in C++. Following the developments in exten...
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ISBN:
(纸本)1581131461
We present the architecture and a performance assessment of an extensible query optimizer written in Venus. Venus is a general-purpose active-database rule language embedded in C++. Following the developments in extensible database query optimizers, first in rule-based form, followed by optimizers written as object-oriented programs, the Venus-based optimizer avails to the advantages of both. Venus' modular structure allows us to go a step further and provide extensibility in search by defining parameterized search components in a declarative form that has the additional effect of integrating heuristic and cost-based optimization. We compare optimizers developed with Volcano, OPT++ and Venus. Venus' optimizing compiler yields code whose performance is comparable with Volcano and OPT++ on smaller queries. The ability to introduce additional pruning heuristics yields better scalability on larger queries. Evaluation of the system using quantitative software metrics supports a claim that the Venus-based optimizer is more easily maintained and extended than are its predecessors.
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