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In this paper, we present a web-based intelligent education system to help students in the context of an AI course. We concentrate on the adaptivity and student evaluation aspects of the system. Adaptivity refers to the capability of the system to adapt teaching to student needs, specified by the student model characteristics. Student evaluation refers to(More)
In this paper, we present an approach that integrates symbolic rules, neural networks and cases. To achieve it, we integrate a kind of hybrid rules, called neurules, with cases. Neurules integrate symbolic rules with the Adaline neural unit. In the integration, neurules are used to index cases representing their exceptions. In this way, the accuracy of the(More)
In this paper, we present the architecture and describe the functionality of a Web-based Intelligent Tutoring System (ITS), which uses neurules for knowledge representation. Neurules are a type of hybrid rules integrating symbolic rules with neurocomputing. The use of neurules as the knowledge representation basis of the ITS results in a number of(More)
Neurules are a kind of hybrid rules integrating neurocomputing and production rules. Each neurule is represented as an adaline unit. Thus, the corresponding neurule base consists of a number of autonomous adaline units (neurules). Due to this fact, a modular and natural knowledge base is constructed, in contrast to existing connectionist knowledge bases. In(More)
An inference engine for a hybrid representation scheme based on neurules is presented. Neurules are a kind of hybrid rules that combine a symbolic (production rules) and a connectionist representation (adaline unit). The inference engine uses a connectionist technique, which is based on the 'firing potential', a measurement of the firing tendency of a(More)
In this paper, we first present and compare existing categorization schemes for neuro-symbolic approaches. We then stress the point that not all hybrid neuro-symbolic approaches can be accommodated by existing categories. Such a case is rule-based neuro-symbolic approaches that propose a unified knowledge representation scheme suitable for use in expert(More)
Rule-based and case-based reasoning are two popular approaches used in intelligent systems. Rules usually represent general knowledge, whereas cases encompass knowledge accumulated from specific (specialized) situations. Each approach has advantages and disadvantages, which are proved to be complementary in a large degree. So, it is well-justified to(More)
In this paper, we present an intelligent system for the diagnosis and treatment of urinary incontinence (UI) for males as well as females, called e-URIN. e-URIN is an intelligent system for diagnosis and treatment of urinary incontinence according to symptoms that are realized in one patient and usually recorded through his clinical examination as well as(More)