Diierent requirements for the representation of the factual knowledge for the use in mechanised reasoning systems are represented. In particular, we distinguish diier-ent types of knowledge: axioms, deenitions (for introducing concepts like \set" or \group") and theorems (for relating the concepts) for formulating concepts and their relationships, as well as proofs, examples and counterexamples...

A long time span often lies between the production (initial configuration) and the reconfiguration of a technical system. During that time new components are invented and related knowledge changes. The goal of this examination is to use the same knowledge base over years. One common way to solve this problem is to integrate a versioning system into the knowledge base. This article however exami...

Past research using a deferred imitation task has shown that 6-month-olds remember a 3-part action sequence for only 1 day. The concept of a time window suggests that there is a limited period within which additional information can be integrated with a prior memory. Its width tracks the forgetting function of the memory. This study asked if retrieving the memory of the modeled actions at the e...

Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. We developed a selective knowledge base of only clinically significant drug alerts and designated only critical-high severity alerts to be interruptive to clinician workflow (a tiered approach). Using this approach, we were able to achieve a 67% clinician acc...

There exist a large number of approaches for prioritization of software requirements. Despite of several empirical studies, there is still a lack of evidence of which approaches that are to prefer, since different studies have resulted in different conclusions. Reasons may be due to differences in contexts, variables measured, and data sets used. This paper presents a research framework for stu...

In this paper, answer set programming and hierarchical knowledge bases are compared as knowledge representation paradigms for representing agent behavior. The comparison is based on two evaluation criteria: (1) comprehensibility (i. e., how easily the represented agent behavior can be comprehended by humans) and (2) reasoning efficiency (i. e., which of the two paradigms allows agents for more ...

Knowledge bases are encountered in different AI areas such as configuration, planning, diagnosis, semantic web, game playing, and others. Very often the amount and arrangement of the elements in the knowledge base outstrips the capability of a knowledge engineer to survey them and to efficiently perform maintenance operations – a situation that triggers an enormous demand of extending and impro...

This paper presents a practical learning-based methodology and agent shell for building knowledge bases and knowledge-based agents, and their innovative application to the development of a critiquing agent for military courses of action, a challenge problem set by DARPA’s High Performance Knowledge Bases program. The agent shell consists of an integrated set of knowledge acquisition, learning a...