Download Free A Step Toward An Intelligent Unix Help System Knowledge Representation Of Unix Help Utilities Book in PDF and EPUB Free Download. You can read online A Step Toward An Intelligent Unix Help System Knowledge Representation Of Unix Help Utilities and write the review.

Abstract: "Because of its wide availability and open architecture, UNIX[superscript TM] provides a suitable and convenient environment for command user interface research. We believe a formal, yet practical, knowledge representation scheme for UNIX utilities is a necessary tool to build higher-level online help and active help systems. We propose a hierarchy of knowledge levels to represent knowledge of UNIX: static objects, command syntax, command synopsis, command semantics and UNIX semantics. We describe how to implement the first three levels using taxonomic classification technology. We illustrate their usefulness by showing how they can be used to correct some non-trivial mistakes made by novice users. The ultimate goal of this research is to realize a UNIX command user interface (UNIX shell) that is knowledgeable enough to give intelligent advice to the user. By intelligent advice, we mean advice of a kind previously available only from human experts."
In this international collection of papers there is a wealth of knowledge on artificial intelligence (AI) and cognitive science (CS) techniques applied to the problem of providing help systems mainly for the UNIX operating system. The research described here involves the representation of technical computer concepts, but also the representation of how users conceptualise such concepts. The collection looks at computational models and systems such as UC, Yucca, and OSCON programmed in languages such as Lisp, Prolog, OPS-5, and C which have been developed to provide UNIX help. These systems range from being menu-based to ones with natural language interfaces, some providing active help, intervening when they believe the user to have misconceptions, and some based on empirical studies of what users actually do while using UNIX. Further papers investigate planning and knowledge representation where the focus is on discovering what the user wants to do, and figuring out a way to do it, as well as representing the knowledge needed to do so. There is a significant focus on natural language dialogue where consultation systems can become active, incorporating user modfelling, natural language generation and plan recognition, modelling metaphors, and users' mistaken beliefs. Much can be learned from seeing how AI and CS techniques can be investigated in depth while being applied to a real test-bed domain such as help on UNIX.
Access Versus Ownership to Word Formation in Language and Computation
Innovations in adult learning are a complex mix of pedagogy, technology, organisation, strategy and vision. In this book, 17 cases representing state-of-the-art design and practice from nine different countries are presented, grouped around the themes of I. Innovative Instrumentation. II. Innovations in Learner Collaboration and III. Innovations in Practice.While all of the cases deal with innovative instrumentation (software or combinations of software and communication technologies), the six cases in section I offer a detailed look at software packages designed for some aspect of the innovation of adult learning, such as reducing information overload by intelligent tools or using a World-Wide Web environment for communication and learning.In section II, a variety of ways to innovate adult learning through collaborative activities are described, including learning scenarios that make effective use of collaboration and the technology and instrumentation that make collaboration at a distance possible.Section III describes innovative learning situations that have been successfully integrated into broad scale field settings, each focusing on a particular situation in which innovative technologies play a part.
Artificial Intelligence and expert systems research, development, and demonstration have rapidly expanded over the past several years; as a result, new terminology is appearing at a phenomenal rate. This sourcebook provides an introduction to artificial intelligence and expert systems, it provides brief definitions, it includes brief descriptions of software products, and vendors, and notes leaders in the field. Extensive support material is provided by delineating points of contact for receiving additional information, acronyms, a detailed bibliography, and other reference data. The terminology includes artificial intelligence and expert system elements for: • Artificial Intelligence • Expert Systems • Natural language Processing • Smart Robots • Machine Vision • Speech Synthesis The Artificial Intelligence and Expert System Sourcebook is compiled from informa tion acquired from numerous books, journals, and authorities in the field of artificial intelligence and expert systems. I hope this compilation of information will help clarify the terminology for artificial intelligence and expert systems' activities. Your comments, revisions, or questions are welcome. V. Daniel Hunt Springfield, Virginia May, 1986 ix Acknowledgments The information in Artificial Intelligence and Expert Systems Sourcebook has been compiled from a wide variety of authorities who are specialists in their respective fields. The following publications were used as the basic technical resources for this book. Portions of these publications may have been used in the book. Those definitions or artwork used have been reproduced with the permission to reprint of the respective publisher.
UC (UNIX Consultant) is an intelligent, natural-language interface that allows naive users to learn about the UNIX operating system. UC was undertaken because the task was thought to be both a fertile domain for Artificial Intelligence research and a useful application of AI work in planning, reasoning, natural language processing, and knowledge representation. The current implementation of UC comprises the following components: A language analyzer, called ALANA, that produces a representation of the content contained in an utterance; an inference component called a concretion mechanism that further refines this content; a goal analyzer, PAGAN, that hypothesizes the plans and goals under which the user is operating; an agent called UCEgo, that decides on UC's goals and proposes plans for them; a domain planner, called KIP, that computes a plan to addressthe user 's request; an expression mechanism, UCExpress, that determines the content to be communicated to the user, and a language production mechanism, UCGen, that expresses UC's response in English. UC also contains a component called KNOME that builds a model of the user's knowledge state with respect to UNIX. Another mechanism, UCTeacher, allows a user to add knowledge of both English vocabulary and facts about UNIX to UC's knowledge base. This is done by interacting with the user in natural language. All these aspects of UC make use of knowledge represented in a knowledge representation system called KODIAK. KODIAK is a relation-oriented system that is intended to have wide representational range and a clear semantics, while maintaining a cognitive ap peal. All of UC's knowledge, ranging from its most general concepts to the content of a particular utterance, is represented in KODIAK.