Focusing on fundamental scientific and engineering issues, this book communicates the principles of building and using knowledge systems from the conceptual standpoint as well as the practical. Previous treatments of knowledge systems have focused on applications within a particular field, or on symbol-level representations, such as the use of frame and rule representations. Introduction to Knowledge Systems presents fundamentals of symbol-level representations including representations for time, space, uncertainty, and vagueness. It also compares the knowledge-level organizations for three common knowledge-intensive tasks: classification, configuration, and diagnosis. The art of building knowledge systems incorporates computer science theory, programming practice, and psychology. The scope of this book is appropriately broad, ranging from the design of hierarchical search algorithms to techniques for acquiring the task-specific knowledge needed for successful applications. Each chapter proceeds from concepts to applications, and closes with a brief tour of current research topics and open issues. Readers will come away with a solid foundation that will enable them to create real-world knowledge systems using whatever tools and programming languages are most current and appropriate.

This textbook is a culmination of multiple efforts of the authors to fill in the gap for offering a required course on Indian Knowledge System (IKS), recently mandated by AICTE. Moreover, the New Education Policy (NEP) has also provided a clear trajectory for imparting IKS in the higher education curriculum, necessitating a book of this kind in several higher education institutions in the country in the days to come. The book seeks to introduce the epistemology and ontology of IKS to the Engineering and Science students in a way they can relate, appreciate and explore further should there be a keen interest in the matter. After a brief section on the key concepts of IKS, the remaining part of the book traces IKS and brings out the applications. After a formal and concise introduction to IKS, the book provides certain foundational concepts applicable across all domains of Science and Engineering. These form the second part. The Science applications are laid out in Part 3, Engineering applications in Part 4 and other important topics in the final part of the book. The authors have rich expertise and background in both 'mainstream issues' and 'traditional knowledge' to present IKS in a contextually relevant fashion. They have delicately balanced the 'why' or 'how' of IKS and the 'what' of IKS. Although the book has been primarily developed for use by the Engineering institutions, the structure and the contents also address the requirement in other University systems (Liberal Arts, Medicine, Science and Management). This textbook incorporates several pedagogical features including a companion website https://www.phindia.com/ introduction_to_indian_knowledge_system that will make learning effective and enjoyable for the students. TARGET AUDIENCE Students at: • Engineering Institutes • Higher Education Institutes

In recent years, knowledge systems have become key areas of concern for researchers, policy-makers and developmental activists. Knowledge Systems and Natural Resources is a unique collection of case studies from Nepal. It provides rich and incisive insights into critical social processes and deliberative governance. It analyses how knowledge is produced, disseminated and applied in various aspects of natural resource governance in Nepal. The book challenges the dichotomy between traditional and scientific knowledge. It proposes to differentiate among systems of knowledge on the basis of political standing of social actors engaged in natural resource governance. It further proposes that change in governance hinges on how the diverse systems of knowledge come into deliberative interface and to what extent the unequal distribution of power and knowledge resources in society constrain the process of deliberation.

Knowledge has only recently been widely recognized as an organizational asset, the effective management of which can afford a firm competitive advantage. This book takes an interdisciplinary approach to knowledge management relating it to business strategy, dynamic capabilities and firm performance. Some of the most eminent scholars in management have contributed to this timely book, including John Seely Brown, Chris Argyris, Georg von Krogh, Soumitra Dutta, Howard Thomas and John McGee, Arie Lewin and Silvia Massini. The book offers practitioners and students alike state of the art research in the field of organizational knowledge and management

The success of diagnostic knowledge systems has been proved over the last decades. Nowadays, intelligent systems are embedded in machines within various domains or are used in interaction with a user for solving problems. However, the development of a knowledge system is still a critical issue. Similarly to projects dealing with customized software at a highly innovative level a precise specification often cannot be given in advance. Moreover, necessary requirements of the knowledge system can be defined not until the project has been started or are changing during the development phase. This thesis motivates that classical, document-centered approaches cannot be applied in such a setting. We introduce an agile process model for developing diagnostic knowledge systems, mainly inspired by the ideas of the eXtreme Programming methodology known in software engineering. The engineering process is supported at a primary level by the introduction of knowledge containers, that define an organized view of knowledge contained in the system. The actual knowledge is acquired and formalized right from start, and the integration to runnable knowledge systems is done continuously in order to allow for an early and concrete feedback. The validity and maintainability of the collected knowledge is ensured by appropriate test methods and restructuring techniques, respectively. Additionally, we propose learning methods to support the knowledge acquisition process sufficiently. The process model and its activities are evaluated in two real life applications: in a medical and in an environmental project the benefits of the agile development are clearly demonstrated.

This volume contains the papers presented at the “Second International S- posium on Foundations of Information and Knowledge Systems” (FoIKS 2002), which was held in Schloß Salzau, Germany from February 20th to 23rd, 2002. FoIKS is a biennial event focusing on theoretical foundations of information and knowledge systems. It aims to bring together researchers working on the theoretical foundations of information and knowledge systems and to attract researchers working in mathematical ?elds such as discrete mathematics, c- binatorics, logics, and ?nite model theory who are interested in applying their theories to research on database and knowledge base theory. FoIKS took up the tradition of the conference series “Mathematical Fundamentals of Database S- tems” (MFDBS) which enabled East-West collaboration in the ?eld of database theory. The ?rst FoIKS symposium was held in Burg, Spreewald (Germany) in 2000. Former MFDBS conferences were held in Dresden (Germany) in 1987, Visegr ́ ad (Hungary) in 1989, and in Rostock (Germany) in 1991. Proceedings of these previous events were published by Springer-Verlag as volumes 305, 364, 495, and 1762 of the LNCS series. In addition the FoIKS symposium is intended to be a forum for intensive d- cussions. For this reason the time slot of long and short contributions is 60 and 30 minutes respectively, followed by 30 and 15 minutes for discussions, respectively. Furthermore, participants are asked in advance to prepare as correspondents to a contribution of another author. There are also special sessions for the pres- tation and discussion of open research problems.

In presented book the Intelligent Open Learning Systems (IOLS) are proposed, described, discussed, and evaluated. The IOLS is a system in which traditional methods of online teaching are enhanced through the use of artificial intelligence and cognitive science. This is the main topic of the book. It consists of ten chapters and is divided into three parts. The first part concentrates on the Open Learning System (OLS) analysis, in particular: the social and educational meanings of the OLS, the new role of the teacher and the new requirements regarding the structure of didactic material. Moreover, the cybernetic model of student, teacher and computer collaboration is presented, the teaching-learning process content and its main characteristics are discussed, and the system based approach to the OLS design is proposed. The second part is focused on the problem of knowledge modeling in the OLS based on the ontology and the competence approaches and leading to the learning object concept and competence management in open systems. The third part describes applications of the OLS in the virtual laboratory for competence transfer, the community-built system of distance learning network, and the AGH student city – the real-life application of the OLS concept. The authors’ research findings presented in the book should be useful in various applications related to knowledge management, e-learning systems and information systems.

CIMA Official Learning Systems are the only textbooks recommended by CIMA as core reading. Written by the CIMA examiners, markers and lecturers, they specifically prepare students to pass the CIMA exams first time. Fully updated to reflect the 2010 syllabus, they are crammed with features to reinforce learning, including: - step by step coverage directly linked to CIMA's learning outcomes - fully revised examples and case studies - extensive question practice to test knowledge and understanding - integrated readings to increase understanding of key theory - colour used throughout to aid navigation * The Official Learning systems are the only study materials endorsed by CIMA * Key sections written by former examiners for the most accurate, up-to-date guidance towards exam success * Complete integrated package incorporating syllabus guidance, full text, recommended articles, revision guides and extensive question practice

Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitive systems. Martin V.