Es-builder Expert System Shell 3.0 Download
Joyce Langwell
I made a simple expert system using ES-Builder. Please click the link to view it. ES-Builder is a web-based expert system shell. There is a tree-based knowledge representation. In ES builder, User Interfaces are also automatically designed. They generate a link as I have shared above and anyone can access it and can use it.
But when I try other ES shells such as JESS, CLIPS & PyKE, I only noticed that there we have to write facts and rules and the program is run on command line upon consulting the Expert System. There is no UI like in ES-Builder.
My question is, is there any way to build UI to the expert systems created by CLIPS/JESS? Or else should I create a web application using another framework like Spring, DotNet, and integrate it with the knowledge base created with CLIPS/JESS?
(I am a bit confused, because according to what I have learned: if we use an expert system shell then we need not program it using languages (such as Prolog). Because the User Interfaces and Inference Engine is already there. What we are remained to do is just to build the knowledge base. Similar to ES builder UI is auto built.)
N2 - Expert Systems (ES) is a branch of Artificial Intelligence (AI) that makes extensive use of specialized knowledge to solve problems at the level of a human expert. It uses a computer program that represents and reasons with knowledge of some specialist subject with a view to solving problems or giving advice. These systems represent a programming methodology by which a computer can be instructed to perform tasks that were previously considered to require the intelligence of a human expert. The development of the Multi-Tenant Database (MTD) adoption framework involved the accumulation of extensive specialised knowledge of experts, hence there is a need for this to be implemented in an ES. This paper presents a forward chaining method used in the implementing of the MTD framework into an expert system. A free web-based expert system shell called ES-BUILDER was adopted. The framework was validated via a survey and analysed with the aid of SPSS software. The findings obtained from the validation procedure indicate that the framework is valuable and suitable for use in practice since the research shows that the majority of respondents accepted the research findings and recommendations for success. Likewise, the ES was also validated using a survey with the majority of participants accepting it and embraces the high level of its usability.
AB - Expert Systems (ES) is a branch of Artificial Intelligence (AI) that makes extensive use of specialized knowledge to solve problems at the level of a human expert. It uses a computer program that represents and reasons with knowledge of some specialist subject with a view to solving problems or giving advice. These systems represent a programming methodology by which a computer can be instructed to perform tasks that were previously considered to require the intelligence of a human expert. The development of the Multi-Tenant Database (MTD) adoption framework involved the accumulation of extensive specialised knowledge of experts, hence there is a need for this to be implemented in an ES. This paper presents a forward chaining method used in the implementing of the MTD framework into an expert system. A free web-based expert system shell called ES-BUILDER was adopted. The framework was validated via a survey and analysed with the aid of SPSS software. The findings obtained from the validation procedure indicate that the framework is valuable and suitable for use in practice since the research shows that the majority of respondents accepted the research findings and recommendations for success. Likewise, the ES was also validated using a survey with the majority of participants accepting it and embraces the high level of its usability.
Abstract:The work of quantifying the problems of abandoned mines is the first step towards the rehabilitation of these mines. As the result, in all countries that have many abandoned mines, researchers and different organizations have been making efforts to develop decision-making tools, methods, and techniques for rehabilitation of abandoned mines. This paper describes the work conducted to incorporate the method for ranking the problems of abandoned mine entries into a rule-based expert system. This is done using the web-based expert system platform provided by expert system (ES)-Builder Shell. The ES is tested by applying it to the case study of the problems of abandoned mine entries in the areas of Giyani and Musina, Limpopo Province of South Africa. This paper gives details of the procedure followed in creating the production rules of the ES for ranking problems of abandoned mine entries (ES-RAME), its attributes, and the results of its application to the selected case study. The use of the ES-RAME is found to be important for setting the objectives and priorities of the rehabilitation of abandoned mine entries. In addition, the incorporation of the ranking method into the expert system ensured that the procedure of the tanking method is clearly communicated and preserved as the rules of the ES. The expert system also has the advantages of being consistent in its guidance, and it gives the user an opportunity to go through the ranking process of the system using any possible fictitious information; this gives the user a feel for the ranking process and the data required when using the ES-RAME. Keywords: abandoned mines; mine entries; expert system; hazard ranking
An expert is also very good at solving particular types of problems, restructuring information in such a way that usually divides a problem into smaller, usually more easily solvable parts. An expert can also find multiple solutions, if they are appropriate, and can justify, verify or at least attach some level of certainty to its solution.
A computer implemented expert system can work continually (24hrs a day) can be duplicated (thus creating many experts), never dies (taking knowledge with it), learns indefinitely (so long as new information is added to the system), always operates at peak performance, and does not suffer form personality incompatibilities. A computer expert system, however, is NOT INTELLIGENT. They may appear to be working intelligently, but that is because they are programmed to emulate human intelligence. All responses and prompts have been painstakingly designed, allowing for near 'natural' interaction. All decisions and conclusions are based on hard and fast rules, and heuristics (rules of thumb).
Typically, expert systems comprise of a KNOWLEDGE BASE (of declarative knowledge - facts; and procedural knowledge -rules) and an INFERENCE ENGINE (which accesses, selects and executes previously programmed rules). The knowledge contained in an expert system is encoded at the time of design implementation and, although it may be updated periodically, it is a 'fixed' or 'hard coded' knowledge base.
Typically, knowledge in expert systems is captured as a collection of IF..THEN rules. Heuristics are educated guesses or rules which are known by experts in the field, and are also used in making inferences with expert systems (an inference is a process where new facts are derived from existing facts).
Each ATTRIBUTE in turn has been divided into at least 2 VALUES ('waterproof eggs' and 'live birth' being examples). You will notice that in the example above, the attributes have been expressed as part of a fact sentence - the values complete these sentences. This is done to make the decision path read more like natural english, and is possible using some expert system shells.
Expert systems need large 'chunks' of knowledge to achieve high levels of performance. A human 'expert' (eg. a chess master) may acquire 50-100000 'chunks of domain specific knowledge, and it may take 10 years of practice to attain.
Expert System Builder (ESB) is a FREEWARE program intended to simplify the development of practical fuzzy decision support systems (or expert systems) that can be used in the day-to-day decision making processes of an organisation. The resultant system may be deployed locally on a single computer or deployed onto the internet
The most important applied area of AI is the field ofexpert systems. An expert system (ES) is a knowledge-based system thatemploys knowledge about its application domain and uses an inferencing (reason) procedureto solve problems that would otherwise require human competence or expertise. The power ofexpert systems stems primarily from the specific knowledge about a narrow domain stored inthe expert system's knowledge base.
It is important to stress to students that expertsystems are assistants to decision makers and not substitutes for them. Expert systems donot have human capabilities. They use a knowledge base of a particular domain and bringthat knowledge to bear on the facts of the particular situation at hand. The knowledgebase of an ES also contains heuristic knowledge - rules of thumb used byhuman experts who work in the domain.
The strength of an ES derives from its knowledgebase - an organized collection of facts and heuristics about the system's domain.An ES is built in a process known as knowledge engineering, during whichknowledge about the domain is acquired from human experts and other sources by knowledgeengineers.
The explanation facility explains how thesystem arrived at the recommendation. Depending on the tool used to implement the expertsystem, the explanation may be either in a natural language or simply a listing of rulenumbers.
1. Combines the facts of a specific case withthe knowledge contained in the knowledge base to come up with a recommendation. In arule-based expert system, the inference engine controls the order in which productionrules are applied (Afired@) and resolves conflicts if more than one rule isapplicable at a given time. This is what Areasoning@ amounts to in rule-based systems.
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