Knowledge Elicitation

Group model building can be used as a tool to increase the efficiency of game development. In a development project done for an Air War College, group model building was used as a core method to create a multiplayer, decision training game. The method made it possible, within two working days, to progress from the first meeting between domain experts and modeller to a tested, multiplayer game. The development work was perceived as involving college instructors in a positive and useful process of knowledge elicitation and sharing. The final product was evaluated by both instructors and students as a suitable tool for decision-making training at strategic level. At the same time the development required very limited use of resources.

This paper presents a baseline perspective of knowledge engineering (KE) methodologies by taking a critical look at the methodological approaches currently used in knowledge engineering domain. A literature review bordering on; the knowledge role concept, knowledge elicitation techniques, and ontological approaches employed in knowledge engineering for the construction of knowledge-based systems (KBSs) was carried out. Journal and conference articles were sourced from multiple journals and research databases and a multi-step manual cross-checking based on carefully selected extraction and quality criteria were employed. The findings of the study show that the existing methodological approaches employed for constructing KBSs in KE is highly deficient and inefficient for solving KE problems under dynamic and uncertain environments. The paper concludes by presenting a strong argument as to why soft systems methodology is best suited for constructing knowledge base systems (KBS) in a spatially distributed, unstructured and shared domain specific context.

This paper is concerned with the use of discourse analysis and observation to elicit expert knowledge. In particular, we describe the use of these techniques to acquire knowledge about expert problem solving in an information provision environment. Our method of analysis has been to make audio-recordings of real-life information interactions between users (the clients) and human intermediaries (the experts) in document retrieval situations. These tapes have then been transcribed and analysed utterance-by-utterance in the following ways: assigning utterances to one of the prespecified functional categories; identifying the specific purposes of each utterance; determining the knowledge required to perform each utterance; grouping utterances into functional and focus-based sequences. The long-term goal of the project is to develop an intelligent document retrieval system based on a distributed expert, blackboard architecture.

Abstract:

This article, written for the Polygraph Journal, is a condensed compilation of a germinal study that provided current successful methods for obtaining confessions during interrogations. The foundation of the study derived from active-duty police detectives that illustrated methods they used to gain confessions from suspects in criminal cases. The study also provided a literature review of past practices of renowned interrogation techniques that collaborated with oral interviews with police investigators from selective east coast and west coast law enforcement agencies.

Lean supply chain management is a relatively new concept resulting from the integration of lean philosophy into supply chain management. Decision making in a lean supply chain context is challenging because of the complexity, dynamics, and uncertainty inherent to both supply networks and the types of waste (defined as any processes, including use of resources, which do not add value to customers). Efficient knowledge management has been identified as one of the key requirements to achieve integrated support for lean supply chain decisions. This paper proposes a decision-focused knowledge framework including a multi-layer knowledge model (to capture the know-why and know-with together with the know-what and know-how), a knowledge matrix for knowledge elicitation, and a decision tree for the design of the knowledge base. A knowledge system for lean supply chain management (KSLSCM) has been developed using artificial intelligence system shells VisiRule and Flex. The KSLSCM has five core components: a supply chain decision network manager, a waste elimination knowledge base, a knowledge refinement module, an inference engine, and a decision justifier. The knowledge framework and the KSLSCM have been evaluated through an industrial decision case. It has been demonstrated through the KSLSCM that the decision-focused knowledge framework can provide efficient and effective support for collaborative decision making in supply chain waste elimination.

Margery J. Doyle retains all Intellectual Property and Copyrights © 2014 for any or all of these works.

ABSTRACT: In order to properly simulate behavior based representations of real red and/or blue force operators through the use of models/agents acting as computer generated forces, it is necessary that the behavioral model receive information about the world including who exists, where they are, and relevant events. This includes not only what the actual hardware platform would receive or be capable of sensing, but also the information a human pilot could capitalize upon; information often obtained through communication channels or via the pilot’s own sensory, perception, knowledge, and/or decision making processes. For example, a pilot receives an air picture from the Air Battle Manager, which is derived via the ABM’s assessment of tactical information. In live and virtual exercises, any additional information a pilot might receive is limited to what the systems on his/her aircraft can sense; limitations not realized by a constructive model connected to the training network. Meaning, a behavior model of an aircraft with a maximum actual radar detection range of 15 miles would, without constraints representative of actual system capabilities, may detect entities outside of its normal range of capability; greatly diminishing external validity, realism, and believability. As such, we are developing a proof-of-concept for a Fighter Combat-Tactical Awareness Capability. This approach involves a model-to-Distributed Interactive Simulation-Environment Abstraction-Tactical Observer Agent to accommodate realistic information sharing with model/system function components. The EA–TOA translates low-level Distributed Interactive Simulation information into objects and then uses filters, based on actual maneuver recognition, hardware and human-in-the-loop oriented capability and limitation parameters, to create a Tactical Awareness Capability; limiting the information available to a model to the semantic/knowledge level of analysis. Herein, the genesis of FC-TAC, realizable through a multi-step data and EA process, syntactic and semantic validation, the application’s generalizability, and an actual proof-of-concept currently in use will be discussed.
Margery J. Doyle retains full Intellectual Property and Copyrights © 2014 for these works.

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case study that was conducted within the logistics unit of Shell Chemicals Europe. The proposed method is based on the classical view by Sprague and Carlson of sequence and interaction of the different phases of decision making in a decision support system and supports Kraljic’s portfolio approach for supplier management. This method aims to help the managers in making decisions on the allocation of volumes to suppliers while simultaneously trying to satisfy conflicting objectives of improvement in benefit and reduction in risk. A mathematical model to struc-ture the problem is presented, knowledge elicited from the managers is used to parameterize the mathemati-cal model and a multi-objective, hi...

A number of social, economic, technological, and scientific trends have led to the emergence of communities of practice centered on the notion of the knowledge-based organization. However, the scientific foundation (knowledge elicitation methodology) and the commercial growth of knowledge management (KM) have largely developed in parallel. So, the creation of human-centered systems faces lingering challenges. In the KM process, company management establishes a program whereby experts who possess valuable ...

This paper presents an efficient approach to training an agent to perform a complex task through demonstration, explanation and supervision. This approach is based on an integration of techniques of multistrategy and apprenticeship learning, knowledge elicitation and programming by demonstration, in a plausible version space framework, and is implemented in Agent-Disciple. Agent-Disciple addresses the complexity of the task training problem

This article presents the development of a group facilitation technique (PROMOD — Procedural Moderation). The author points toward the importance of integrating theoretical assumptions, theory testing and basic empirical research with practical application. The results are based on the observation of various three-member task groups faced with a complex non-heureka problem. These comprise naturally interacting groups, simple arithmetic assembled groups of individuals without any interaction (synthetic groups), and groups in which a group technique of reduced interaction which focuses on individual contribution through facilitated knowledge elicitation is applied.The task involves decisions on what to do after a plane crash and ranking objects with regard to their importance for survival in an alarming situation (Lafferty & Pond, 1974). The group decision quality is determined by relating to conclusions reached by an independent expert. Results indicate that the observed teams perfor...

Ce document développe un ensemble de graphes patron de connaissances pour analyser et indexer des corpus audiovisuels (vidéos) thématisant les sujets qui font partie du domaine de la diversité linguistique et culturelle. Les graphes patrons spécifiés intègrent des parcours (partiellement linéaires) utilisés par les analystes des corpus audiovisuels dans leur travail concret de description et de documentation d'un matériel audiovisuel.

L'ontologie qui sert de référence est la première version de l’ontologie ASA (Atelier de Sémiotique Audiovisuelle pour l’analyse de corpus de vidéos en SHS), réalisée dans le cadre des deux projets de R&D – LOGOS (projet européen financé dans le cadre du 6ème FP entre 2006 et 2009) et SAPHIR (projet français financé par l’ANR entre 2006 et 2009). Cette première version est décrite dans : P. Stockinger, The PCI Ontology. Presentation and discussion of an ontology for the description and indexing of audiovisual resources in the field of cultural heritage of minorities and indigenous people; Paris, ESCoM-AAR 2007 (DOI: 10.13140/2.1.1180.5129).

L’ontologie ASA était l’objet de plusieurs projets de recherche et de publications et servait surtout à l’analyse (classification, description, interprétation, …) de corpus audiovisuels dans le cadre du Programme AAR (Archives Audiovisuelles de la Recherche). Depuis 2015, elle fait partie de la plateforme Campus AAR, déployée sur les serveurs du CCSD/HAL et mise à la disposition de la communauté des chercheurs et enseignants en SHS.

Organisations across sectors such as aerospace, construction, defence and health care are increasingly being asked not only to provide products in the first instance, but also to support them throughout their service life. Virtually all engineering products are designed using Computer Aided Design (CAD) analysis and simulation systems. Today’s CAD systems are excellent tools for recording the end result of a design process, particularly at the detail design stage. However, they are poor at capturing the rationale and underlying intent within the design itself. If CAD systems could automatically capture the reasoning underlying the development of a design then- even years after the original design had been created- engineers could better understand the consequences of potential upgrades and modifications. In order to study this hypothesis, the authors identified the game software CBBC BAMZOOKi as a useful experimental system for the automated capture of design knowledge. This paper e...

This paper addresses human resources utilization at the university environment. We address the design issues of e-learning courses that can capture the teacher knowledge. The underlying objective is that e-learning is a key knowledge and major resources for many universities. Therefore, the design of e-learning should be an important part of the university knowledge management process. Teachers ' knowledge in any important topic or field should be managed in a way that the university can benefit from it in case of teacher leaving or retired. Hence, intellectual personal knowledge management will be explored through the development of e-learning systems. Some concepts from the Artificial Intelligence field can be used in developing such systems. The potential for utilizing human knowledge in the university environment will optimize the resources and can be of cost effective and quality assurance factors and provide the university with a sustainable competitive advantage. Assurin...

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, ...

The 'Knowledge Engineer's Assistant'(KEATS) is a software environment suitable for constructing knowledge-based systems. In this paper, we discuss its role in supporting the knowledge engineer in the tasks of knowledge elicitation and domain understanding. KEATS is based upon our own investigations of the behaviour and needs of knowledge engineers and provides two enhancements to other modern 'shells'.'toolkits', and 'environments' for knowledge engineering:(i) transcript analysis facilities, and (ii) a ...

The past 25 years have experienced a substantial amount of research on safety communications, more specifically, warnings. This article focuses on the most important factors in designing effective warnings. The warning process is modeled in three stages. Effective warnings attract attention; elicit knowledge, and enable compliance behavior. Two main categories are design factors and non-design factors. Non-design factors include the effects of target audience and situational factors. For attention, important design factors are size, color/contrast, signal word, graphics, and format. The non-design factors for attention include context, location, and distraction. Design factors affecting the knowledge and compliance stages include explicit wording and pictorials to provide hazard, consequences and instructional content. Non-design factors for the knowledge stage include familiarity and perceived hazard. Non-design factors for the compliance stage include modeling the behavior of others and cost of compliance. The research literature offers practical design recommendations to aid application decisions.