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Machine Learning
The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed i...
Machine Learning
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Ea...
Machine Learning
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Ea...
Changes of Problem Representation
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible f...
Planning and Learning by Analogical Reasoning
This research monograph describes the integration of analogical and case-based reasoning into general problem solving and planning as a method of speedup learning. The method, based on derivational analogy, has been fully implemented in PRODIGY/ANALOGY and proven in practice to be amenable to scaling up, both in terms of domain and problem complexity. In this work, the strategy-level learning process is cast for the first time as the automation of the complete cycle of construction, storing, retrieving, and flexibly reusing problem solving experience. The algorithms involved are presented in detail and numerous examples are given. Thus the book addresses researchers as well as practitioners.
Natural Language Parsing Systems
Up to now there has been no scientific publication on natural lan guage research that presents a broad and complex description of the current problems of parsing in the context of Artificial Intelli gence. However, there are many interesting results from this domain appearing mainly in numerous articles published in pro fessional journals. In view of this situation, the objective of this book is to enable scientists from different countries to present the results of their research on natural language parsing in the form of more detailed papers than would be possible in professional jour nals. This book thus provides a collection of studies written by well known scientists whose earlier publi...
Restricted-Orientation Convexity
Restricted-orientation convexity is the study of geometric objects whose intersections with lines from some fixed set are connected. This notion generalizes standard convexity and several types of nontraditional convexity. The authors explore the properties of this generalized convexity in multidimensional Euclidean space, and describ restricted-orientation analogs of lines, hyperplanes, flats, halfspaces, and identify major properties of standard convex sets that also hold for restricted-orientation convexity. They then introduce the notion of strong restricted-orientation convexity, which is an alternative generalization of convexity, and show that its properties are also similar to that of standard convexity.
Machine Learning
Explains the major paradigms for machine learning: inductive approaches, explanation-based learning, genetic algorithms and connectionist learning methods.
Topic Detection and Tracking
Topic Detection and Tracking: Event-based Information Organization brings together in one place state-of-the-art research in Topic Detection and Tracking (TDT). This collection of technical papers from leading researchers in the field not only provides several chapters devoted to the research program and its evaluation paradigm, but also presents the most current research results and describes some of the remaining open challenges. Topic Detection and Tracking: Event-based Information Organization is an excellent reference for researchers and practitioners in a variety of fields related to TDT, including information retrieval, automatic speech recognition, machine learning, and information extraction.
Organization and Decision Theory
Ira Horowitz Depending upon one's perspective, the need to choose among alternatives can be an unwelcome but unavoidable responsibility, an exciting and challenging opportunity, a run-of-the-mill activity that one performs seem ingly "without thinking very much about it," or perhaps something in between. Your most recent selections from a restaurant menu, from a set of jobs or job candidates, or from a rent-or-buy or sell-or-Iease option, are cases in point. Oftentimes we are involved in group decision processes, such as the choice of a president, wherein one group member's unwelcome responsibility is another's exciting opportunity. Many of us that voted in the presidential elections of both...
