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| Author | : Susan F. Chipman |
| Publisher | : |
| Total Pages | : |
| Release | : 1993 |
| Genre | : Knowledge acquisition (Expert systems) |
| ISBN | : |
| Author | : Alan L. Meyrowitz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 341 |
| Release | : 2007-08-19 |
| Genre | : Computers |
| ISBN | : 0585273669 |
One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact of successful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain about the methods by which machines and humans might learn, significant progress has been made.
| Author | : Susan F. Chipman |
| Publisher | : |
| Total Pages | : |
| Release | : 1993 |
| Genre | : Knowledge acquisition (Expert systems) |
| ISBN | : |
| Author | : Brian R. Gaines |
| Publisher | : |
| Total Pages | : 418 |
| Release | : 1990 |
| Genre | : Computers |
| ISBN | : |
This book presents a broad view of the fundamental issues involved in knowledge acquisition and their place in knowledge-based systems development. The book covers theory based methods and problem modeling approaches to provide a strong theoretical and methodological basis for practical and effective knowledge acquisition techniques.
| Author | : Susan Chipman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 347 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461531721 |
One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact ofsuccessful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain aboutthe methods by which machines and humans might learn, significant progress has been made.
| Author | : N. Jayashri |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
Knowledge acquisition includes complex intellectual processes: recognition, learning, correspondence, affiliation, and reasoning. The term knowledge is additionally used to mean the pure comprehension of a subject with the capacity to utilize it for a particular reason. By definition, knowledge can be partitioned into two sorts: inferred and express knowledge. Implicit knowledge will be the knowledge that individuals convey in their brains and is, subsequently, hard to get to. Inferred knowledge is viewed as more significant in light of the fact that it gives setting to individuals, spots, thoughts, and encounters. Powerful exchange of implied knowledge by and large requires broad individual contact and trust. In this review, we are going to see the activities, methodologies, and tools, and some auto-generated database query examples, created for knowledge acquisition, can be altered and stretched out to help scholarly foundations with knowledge management.
| Author | : Karen L. McGraw |
| Publisher | : |
| Total Pages | : 408 |
| Release | : 1989 |
| Genre | : Computers |
| ISBN | : |
This book presents a practical view of the knowledge acquisition process, its methodologies and techniques, in order to enable readers to develop expert systems knowledge bases more effectively. It strikes a balance between presenting (1) summaries of research in the field of knowledge acquisition and (2) methodologies and techniques that have been applied and tested on numerous programs in various contexts. Written for novice knowledge engineers or others tasked with acquiring knowledge for the systematic development of expert systems. The presentation of the material does not presume a background in either computer science or artificial intelligence.
| Author | : A. Kidd |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 203 |
| Release | : 2012-12-06 |
| Genre | : Psychology |
| ISBN | : 1461318238 |
Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.
| Author | : Wesley A. Hoover |
| Publisher | : Springer Nature |
| Total Pages | : 279 |
| Release | : 2020-06-09 |
| Genre | : Education |
| ISBN | : 3030441954 |
This book serves as a succinct resource on the cognitive requirements of reading. It provides a coherent, overall view of reading and learning to read, and does so in a relatively sparse fashion that supports retention. The initial sections of the book describe the cognitive structure of reading and the cognitive foundation upon which that structure is built. This is followed by discussions of how an understanding of these cognitive requirements can be used in practice with standards, assessments, curriculum and instruction, to advance the teaching of reading and the delivery of interventions for students who encounter difficulties along the way. The book focuses on reading in English as its exemplar, but shows how its framework can be adapted to understand the broad cognitive requirements for reading and learning to read in any phonologically-based orthography. It provides a way for reading professionals to think about reading and its development and gives them mechanisms that, coupled with such understanding, will help them link what children must know to become strong readers to what teaching can best provide through the competent use of available tools. In this way, the book will help reading professionals be both efficient and effective in what they provide all their students and be much better equipped to support those students who struggle to learn to read.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 347 |
| Release | : 2018-09-27 |
| Genre | : Education |
| ISBN | : 0309459672 |
There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.
