Consensus : a planning protocol for cooperating expert systems

Planning is an important aspect of Distributed Problem Solving. Several approaches have been taken by researchers towards planning. In this thesis, we propose a distributed planning protocol titled Consensus. Consensus is useful in a situation where several expert systems cooperate to solve a problem. It is also applicable in solving ill-structured problems. The set of expert systems that plan using Consensus is called a Consensus Group. Each expert system in a Consensus Group makes a Proposal, from which the Final Plan is generated. The proposed protocol has a potential to minimize the cost of planning because negotiation is avoided. It is implemented and experimentally analyzed. For the purpose of analysis, four metrics were defined and a proposal generator was developed which simulates the expert systems creating their proposals. As a part of Consensus, three alternative heuristics were examined to overcome the computational complexity of a backtracking approach for the generation of the Final Plan. The experimental studies indicate the relative trade-off between the complexity of planning and the quality of the plan with respect to these heuristics. The experimental results and conclusions are presented in the thesis

Integrating STEMM in Higher Education: a proposed curriculum development framework

[EN] Educational systems around the world are trying to grapple with the need forexperts in science, technology, engineering, mathematics and medicine (STEMM),who have expert knowledge and combined skills for working in collaborativeteams to find solutions to local and global issues. Employers seek disciplinaryexperts as well as people who can act as connectors for groups and ideas and whoshare and communicate them effectively. Integration of the STEMM disciplineswithin teaching programmes is in its infancy, but there is recognition for providingextraordinary experiences in learning that develop collaboration and synthesis ofdivergent ways of thinking. A framework is presented for designing integratedSTEMM course work in higher education. It includes authentic, student-centered,evidence-based, inquiry, problem-based learning through situated, immersive andexperiential approaches that can support the deliberate development of skills forintegrating thinking, problem-solving and for creating humanistic solutions forlocal and global issues.Conner, L. (2020). Integrating STEMM in Higher Education: a proposed curriculum development framework. En 6th International Conference on Higher Education Advances (HEAd'20). Editorial Universitat Politècnica de València. (30-05-2020):353-360. https://doi.org/10.4995/HEAd20.2020.11058OCS35336030-05-202

The construction of global management consulting - a study of consultancies’ web presentations

Management consulting increasingly appears as a global endeavour as reflected in the increasing dominance of a few large, global management-consulting firms. However, features of the consulting service (e.g. its immaterial and interactional character) as well as aspects of management (e.g. its cultural anchoredness) highlight the locality of management consulting. In this paper we approach this tension between the global and the local by seeing consulting as involving the creation of generalised myths. More specifically, we ask the question: How do global consulting companies construct the viability and desirability of their services? Based on a view of management consultants as mythmakers, we study the argumentation on corporate web sites of four leading global consultancies in five different countries. Applying a framework based on the sociology of translation, we analyze the translation strategies used in making the service of global consultancies both viable and indispensable. We find that the need for consultants is to a large extent constructed through defining management as an expert activity, thus creating a need for external advisors possessing globally applicable expert knowledge. In this effort, the consultants ally with three widely spread rationalized managerial myths – the rationality myth, the globalization myth and the universality myth. We conclude, that global consulting firms are actively involved in creating and reinforcing the very same institutions, which are the prerequisites for their future success.management consulting; globalization; myth making

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version