Knowledge representation in human problem solving: implications for expert system design

The study focuses on the identification of the underlying representational properties of human problem solving and their application to expert systems. In this study the interaction between problem representation (procedural, conceptual, unstructured) and problem type (transformation, arrangement, inducing structure) was observed. The results of this study indicate partly that quantitative and qualitative differences in problem-solving performance can be attributed to the form of knowledge representation employed by the problem solver. It is suggested that modularized expert systems could be designed with different problem-solving modules organized by problem characteristics or type, exploiting the representational differences identified in this study.     

Fuzzy expert system for solving lost circulation problem

Lost circulation is the most common problem encountered while drilling oil wells. This paper describes a distributed fuzzy expert system, called Smart-Drill, aimed in helping petroleum engineers to diagnose and solve lost circulation problems. To represent and manipulate perception-based evaluations of uncertainties of facts and rules, the expert system uses an uncertainty model with qualitative scales of plausibility values and multi-set-based fuzzy algebra of strict monotonic operations. Its realization in inference procedures permits taking into account the change of plausibility of premises in expert systems rules. Original tools like CAPNET Expert System Shell, Knowledge Acquisition Tool and WITSML Converter implementing the proposed model were used for the development of the Smart-Drill. Overall, the system architecture is discussed and implementation details are provided. Both desktop and Web-based implementations permit petroleum engineers benefit from the system working out in the field. The system is currently at field testing phase in PEMEX, Mexican Oil Company.     

A customized network diagnostic expert system based on general diagnostic strategies

The objective of this research is to investigate the common link in diagnostics of different networks. Are there any underlying common expertise and strategies that are applicable to various connection-based networks? If so, how is the general expertise related to network-specific expertise? Why is it significant to identify and figure out the general expertise? To support our method, we developed an expert system which helps to interpret the alarms delivered from a multiplexer network, determine the faulty behavior of the network, and offer recovery suggestions. Our work classifies the diagnostic expertise into (i) general expertise and (ii) customized or network-specific expertise. The former consists of certain general strategies and common sense in network diagnostics, while the latter consists of specific technology know-how of a network built with a particular product family of multiplexers. Since the general expertise is also applicable to other types of connection-based networks, it is hoped that our work can provide a foundation to build other network diagnostic expert systems.     

A dynamic and automatic traffic light control expert system for solving the road congestion problem

Traffic congestion is a severe problem in many modern cities around the world. To solve the problem, we have proposed a framework for a dynamic and automatic traffic light control expert system combined with a simulation model, which is composed of six submodels coded in Arena to help analyze the traffic problem. The model adopts interarrival time and interdeparture time to simulate the arrival and leaving number of cars on roads. In the experiment, each submodel represents a road that has three intersections. The simulation results physically prove the efficiency of the traffic system in an urban area, because the average waiting time of cars at every intersection is sharply dropped when the red light duration is 65 s and the green light time duration is 125 s. Meanwhile, further analysis also shows if we keep the interarrival time of roads A, B, and C, and change that of roads D, E, and F from 1.7 to 3.4 s and the interdeparture times at the three intersections on roads A, B, and C are equal to 0.6 s, the total performance of the simulation model is the best. Finally, according to the data collected from RFID readers and the best, second and third best traffic light durations generated from the simulation model, the automatic and dynamic traffic light control expert system can control how long traffic signals should be for traffic improvement.     

A model-based expert system for digital system design

An expert system that generates digital system design from high-level specifications is described. It is called MBESDSD, short for model-based expert system for automated digital systems. The system is based on a three-phase model of digital system design. First, the high-level behavioral specifications are translated into a sequence of primitive behavioral operations. Next, these primitive operations are grouped to form intermediate-level behavioral functions. Finally, structural function modules are selected to implement these functions. The advantages of this model-based reasoning technique is that more design solutions are possible and the design is easier to optimize. The design of a popular peripheral device, the ART asynchronous receiver/transmitter, is used to demonstrate the proposed design process using MBESDSD     

A generalized expert system for database design

Generalized Expert System for Database Design (GESDD) is a compound expert system made up of two parts: (1) an expert system for generating methodologies for database design, called ESGM; and (2) an expert system for database design, called ESDD. ESGM provides a tool for the database design expert to specify different design methodologies or to modify existing ones. The database designer uses ESDD in conjunction with one of these methodologies to design a database starting from the requirement specification phase and producing a logical schema in one of the well-known data models, namely, the hierarchical data model, the network data model, or the relational data model. The system is evolutive in the sense that an existing methodology can be modified or a novel methodology can be added to the existing ones. GESDD is a menu-driven system and it is coded in Prolog     

Representation of models for expert problem solving in physics

A computer program, APEX, is proposed to investigate idealized formal models representing physics problems. Two types of models are defined: canonical physical objects and physical models. During problem solving, the problem is represented as a data connection network, which is progressively augmented by these models in the form of additional network elements. APEX employs views as a representational framework for connecting the initially informal objects to the formal models of the domain. The view framework supports multiple representations (e.g., viewing many objects as a single canonical physical object), handling of incompletely specified problems, and invertibility of the views. This computational framework provides a powerful representational mechanism that allows a finite set of physical principles to be applied to a potentially infinite variety of problems. As a knowledge engineering technique, views allow general principles to be applied to a variety of objects whose representations differ     

An expert system for general symbol recognition

An expert system for analysis and recognition of general symbols is introduced. The system uses the structural pattern recognition technique for modeling symbols by a set of straight lines referred to as segments. The system rotates, scales and thins the symbol, then extracts the symbol strokes. Each stroke is transferred into segments (straight lines). The system is shown to be able to map similar styles of the symbol to the same representation. When the system had some stored models for each symbol (an average of 97 models/symbol), the rejection rate was 16.1% and the recognition rate was 83.9% of which 95% was recognized correctly. The system is tested by 5726 handwritten characters from the Center of Excellence for Document Analysis and Recognition (CEDAR) database. The system is capable of learning new symbols by simply adding their models to the system knowledge base.     

Ex-W-Pert system: A Web-based distributed expert system for groupware design

The World Wide Web (Web) allows people at remotely located sites to communicate and share their ideas using a common communication protocol. A common use of the Web system is running a client application, using a browsing tool, by pointing to a local or proxy server to browse data written in the hypertext format that contains anchors that address other URLs. In this paper a new application of the Web system for sharing knowledge-based systems and groupware development activities is introduced. An architecture for a Web-based Distributed Expert System (Ex-W-Pert System) is proposed and an implementation of the proposed architecture in groupware design is demonstrated. The resources and knowledge bases are distributed and can be accessed through the internet.     

Mixed method for solving the general convex programming problem

Conclusion Let us return to the claim that we made at the beginning: given the existing level of computers, computational mathematics must not ignore new opportunities for finding results that have been impossible until very recently. In our view, the proposed mixed method is consistent with technological progress: all known problems have been solved in acceptable time, and not in a single case has the method failed to produce a solution. Although we can always dispute claims of the kind made above, our calculations nevertheless convince that the algorithms proposed in this article may be used to solve a fairly broad class of problems, and in particular semidefinite programming problems [7, 17]. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 121–134, July–August, 1998.     

BDES: A bridge design expert system

The expert system described here designs superstructures for small to medium span highway bridges. The system addresses a domain within the engineering design consultation paradigm. It is installed in a personal microcomputer environment. This paper examines the nature of the bridge design domain as practiced in the United States and its suitability for expert system application. The architecture, the context structure, the knowledge base, the control module, and the implementation of the expert system are presented.     

用于控制系统实时监控的专家系统设计

在某型装备的大型指挥控制系统中,电路节点错综复杂,由其中某些节点的短路或断路可能导致很多故障.在实际的操作中,由于需要进行实时控制,必须能够及时发现并解决问题.本文提出了一种基于故障树分析和统计概率的模块化专家系统,作为此大型指挥控制系统电路的故障实时监测之用.     

A knowledge sorting process for a product design expert system

Knowledge sorting is one way to organize the knowledge acquired from the domain expert(s) and various sources. Well-organized knowledge representation will make rule extraction much easier. This paper describes a knowledge sorting process that was developed to facilitate the rule extraction for a product design expert system. The process capitalizes on the relationships between design attributes and factors, dependent and independent variables, and consists of three stages: identification of knowledge sources, generation of taxonomic trees, and organization of acquired knowledge. An example applies the sorting process to the development of an expert system for the design of wood head golf clubs.     

An approach of implementing general learning companions for problem solving

Adding a learning companion, a computer simulated social agent, to a computer based learning system can enhance its educational value by enriching the way in which the computer and the user interact. This paper presents a novel simulation approach, named General Companion Modeling (referred to hereinafter as GCM), to implement learning companions in a general problem-solving domain. DwestAgent, a learning companion system, is also implemented using the GCM approach to demonstrate the feasibility of the proposed approach. In addition, the approach can help developers of learning companions clarify implementation issues and requirements involved in simulating: (1) domain competencies, (2) learning competencies, (3) behaviors as a peer tutor, and (4) behaviors as a peer tutee of a learning companion. Using GCM, one can simulate learning companions with various characteristics by adjusting parameters within the proposed simulation framework.     

An expert system for design for robotic assembly

In recent years, due to the various advantages associated with automation and robotics, much work has been done in developing robotic systems for assembly operations. Since part design plays a major role in assembly, this paper deals with the design of parts for ease of robotic assembly. Considerable knowledge is available in the form of design for robotic assembly rules. In addition, a large amount of data is required for decisions regarding suitability of parts for robotic assembly. The implementation of design for robotic assembly rules would be much easier with the help of an expert system, which would guide the designer toward choosing the design alternative that can best facilitate ease of assembly from a robotic point of view.To this end, a prototype expert system for design for robotic assembly is developed and presented in this paper. The expert system was implemented as a production system, which consists of rules and Object-Attribute-Value (O-A-V) triplets to represent domain knowledge. In order to best utilize the domain specific knowledge, a state space search-based inference mechanism was employed. The implementation of the prototype system is illustrated with examples.     

The general problem solving algorithm and its implementation

By generalising problem solving techniques such as divide-and-conquer, dynamic programming, tree and graph searching, integer programming and branch-and-bound, a general problem solving algorithm is deduced. Various examples of the use of this algorithm are given and its implementation on both sequential and parallel machines, such as the cosmic cube, is discussed.     

Using an expert system for design diagnosis and design synthesis

Abstract This paper describes the concepts which allow an expert system to be used for both design diagnosis and design synthesis. An example of the implementation of these concepts is presented in the domain of preliminary design of domestic kitchens in the expert system PREDIKT. PREDIKT carries out both design diagnosis and design synthesis using the same knowledge base and utilises an existing expert system shell which has forward- and backward-chaining capabilities. The significance of graphical interaction with expert systems in design domains is demonstrated.     

A modified PSO algorithm with dynamic parameters for solving complex engineering design problem

This paper proposed a new approach of particle swarm optimization (PSO). The proposed modified PSO algorithm is equipped with some specially designed mechanisms of adaptively updating algorithm parameters to preserve the diversity of the swarm and to keep the balance between exploration and exploitation searches. All these mechanisms help the algorithm to avoid the premature convergence and to strengthen its robustness. Experiments are conducted on different complicated, unimodal and multimodal test functions, as well as a typical engineering inverse problem, the TEAM Workshop problem 22. The numerical results illustrate that the proposed PSO shows better performance as compared to other well developed evolutionary algorithms.     

ROGET: A knowledge-based system for acquiring the conceptual structure of a diagnostic expert system

This paper describes ROGET, a knowledge-based system that assists a domain expert with an important design task encountered during the early phases of expert-system construction. ROGET conducts a dialogue with the expert to acquire the expert system's conceptual structure, a representation of the kinds of domain-specific inferences that the consultant will perform and the facts that will support these inferences. ROGET guides this dialogue on the basis of a set of advice and evidence categories. These abstract categories are domain independent and can be employed to guide initial knowledge acquisition dialogues with experts for new applications. This paper discusses the nature of an expert system's conceptual structure and describes the organization and operation of the ROGET system that supports the acquisition of conceptual structures.