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     

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     

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     

A workplace design expert system

Although there is an abundance of reference material available, most facility design engineers lack the proficiency required to design ergonomically sound workplaces. This may be due to several factors. This paper presents an initial knowledge-based system to assist a design engineer in achieving an ergonomic workplace design. The developed system is, in reality, a subsystem consisting of the primary module of the knowledge base as a prototype. The root context, Dimensional Design, was selected for prototyping using the Texas Instruments Personal Consultant. A total of 41 parameters were defined for use by the prototype with 13 of those being goal parameters. In addition 57 rules are imbedded into the system.     

A grid-enabled problem solving environment for parallel computational engineering design

This paper describes the development and application of a piece of engineering software that provides a problem solving environment (PSE) capable of launching, and interfacing with, computational jobs executing on remote resources on a computational grid. In particular it is demonstrated how a complex, serial, engineering optimisation code may be efficiently parallelised, grid-enabled and embedded within a PSE. The environment is highly flexible, allowing remote users from different sites to collaborate, and permitting computational tasks to be executed in parallel across multiple grid resources, each of which may be a parallel architecture. A full working prototype has been built and successfully applied to a computationally demanding engineering optimisation problem. This particular problem stems from elastohydrodynamic lubrication and involves optimising the computational model for a lubricant based on the match between simulation results and experimentally observed data.     

A simple knowledge system environment for engineering problem solving

In this paper, we describe Spartan, a simple environment for developing engineering knowledge systems. The design of Spartan is motivated by the observation that many development environments incur computational overhead that buy us largely unneeded sophistication. Spartan provides only a simple set of building blocks but offers a convenient way to extend its functionalities. We offer both anecdotal and analytical support for some example applications constructed using Spartan. We conclude that Spartan can be used to construct some fairly straightforward knowledge systems. A more surprising result is that even some moderately large knowledge systems can be constructed using Spartan.     

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.     

A reasoning method for a ship design expert system

Abstract: The ship design process is a highly data‐oriented, dynamic, iterative and multi‐stage algorithm. It utilizes multiple abstraction levels and concurrent engineering techniques. Specialized techniques for knowledge acquisition, knowledge representation and reasoning must be developed to solve these problems for a ship design expert system. Consequently, very few attempts have been made to model the ship design process using an expert system approach. The current work investigates a knowledge representation–reasoning technique for such a purpose. A knowledge‐based conceptual design was developed by utilizing a prototype approach and hierarchical decompositioning. An expert system program called ALDES (accommodation layout design expert system) was developed by using the CLIPS expert system shell and an object‐oriented user interface. The reasoning and knowledge representation methods of ALDES are explained in the paper. An application of the method is given for the general arrangement design of a containership.     

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.     

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.     

Assessing problem solving in expert systems using human benchmarking

The human benchmarking approach attempts to assess problem solving in expert systems by measuring their performance against a range of human problem-solving performances. We established a correspondence between functions of the expert system GATES and human problem-solving skills required to perform a scheduling task. We then developed process and outcome measures and gave them to people of different assumed problem-solving ability. The problem-solving ability or “intelligence” of this expert system is extremely high in the narrow domain of scheduling planes to airport gates as indicated by its superior performance compared to that of undergraduates, graduate students and expert human schedulers (i.e. air traffic controllers). In general, the study supports the feasibility of using human benchmarking methodology to evaluate the problem-solving ability of a specific expert system.     

A personal perspective on problem solving by general purpose solvers

To solve the problems that abound in real‐world applications, we are proposing an approach of using general‐purpose solvers, as we cannot afford to develop special‐purpose algorithms for all individual problems. The existing general‐purpose solvers such as linear programming and integer programming are very useful but not sufficient. To improve the situation, we have developed solvers for other standard problems such as the constraint satisfaction problem and the resource‐constrained project scheduling problem among others. In this article, we describe why general‐purpose solvers are needed, what kinds of solvers we considered, how they were developed and where they have been applied.     

"MDZY型，冲压模方案设计专家系统的设计与实现

作为一种先进的金属零件加工方法,冲压生产在工业领域中已经得到了广泛的应用,但其生产效率的进一步提高却由于冲压模具设计的复杂性和耗时性而受到了较大程度制。CAD技术的引入虽然简化了图形的绘制和处理工作,但对冲模设计当中普遍存在的推理、判断等非数值问题却无能为力。文中利用人工智能技术,在Visual C 5．0环境下实现了一个冲压模方案设计专家系统,用来帮助设计者在模具设计前期完成合理的方案设计。系统在执行设计任务时采用了实例匹配和归纳推理两种不同手段,系统中的设计知识分别采用了数据库记录、链表以及集成了框架、规则和方法的对象等多种形式来表示,各类知识的学习和修改采用了包括神经网络在内的多种机制。