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One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution. Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.
This book lends insight into solving some well-known AI problems using the most efficient problem-solving methods by humans and computers. The book discusses the importance of developing critical-thinking methods and skills, and develops a consistent approach toward each problem. This book assembles in one place a set of interesting and challenging AI–type problems that students regularly encounter in computer science, mathematics, and AI courses. These problems are not new, and students from all backgrounds can benefit from the kind of deductive thinking that goes into solving them. The book is especially useful as a companion to any course in computer science or mathematics where there are interesting problems to solve. Features: •Addresses AI and problem-solving from different perspectives •Covers classic AI problems such as Sudoku, Map Coloring, Twelve Coins, Red Donkey, Cryptarithms, Monte Carlo Methods, Rubik’s Cube, Missionaries/Cannibals, Knight’s Tour, Monty Hall, and more •Includes a companion disc with source code, solutions, figures, and more •Offers playability sites where students can exercise the process of developing their solutions •Describes problem-solving methods that might be applied to a variety of situations eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected].
Thinking and Problem-Solving presents a comprehensive and up-to-date review of literature on cognition, reasoning, intelligence, and other formative areas specific to this field. Written for advanced undergraduates, researchers, and academics, this volume is a necessary reference for beginning and established investigators in cognitive and educational psychology. Thinking and Problem-Solving provides insight into questions such as: how do people solve complex problems in mathematics and everyday life? How do we generate new ideas? How do we piece together clues to solve a mystery, categorize novel events, and teach others to do the same? Provides a comprehensive literature review Covers both historical and contemporary approaches Organized for ease of use and reference Chapters authored by leading scholars
Design Problem Solving: Knowledge Structures and Control Strategies describes the application of the generic task methodology to the problem of routine design. This book discusses the generic task methodology and what constitutes the essence of the Al approach to problem solving, including the analysis of design as an information processing activity. The basic design problem solving framework, DSPL language, and AIR-CYL Air cylinder design system are also elaborated. Other topics include the high level languages based on generic tasks, structure of a Class 3 design problem solver, and failure handling in routine design. The conceptual structure for the air cylinder and improvements to DSPL system support are likewise covered in this text. This publication is beneficial to students and specialists concerned with solving design problems.
Machine learning is an emerging area of computer science that deals with the design and development of new algorithms based on various types of data. Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques addresses the complex realm of machine learning and its applications for solving various real-world problems in a variety of disciplines, such as manufacturing, business, information retrieval, and security. This premier reference source is essential for professors, researchers, and students in artificial intelligence as well as computer science and engineering.
Problem-solving strartegies and the nature of Heuristic informatio n.Heuristics and problem representations. Basic Heuristic-Search procedures. Formal properties of Heuristic methods. Heuristics viewed as information provided by simplified models. Performance analysis of Heuristic methods. Abstract models for quantitative performace analysis. Complexity versus precision of admissible Heuristics. Searching with nonadmissible Heuristics. Game-playing programs. Strategies and models for game-playing programs. Performace analysis for game-searching strategies. Decision quality in game searching. Bibliography. Index.
This book shows how collective intelligence combined with new technologies can help us solve the world's biggest problems.
This volume presents a state-of-the-science review of the most promising current European research -- and its historic roots of research -- on complex problem solving (CPS) in Europe. It is an attempt to close the knowledge gap among American scholars regarding the European approach to understanding CPS. Although most of the American researchers are well aware of the fact that CPS has been a very active research area in Europe for quite some time, they do not know any specifics about even the most important research. Part of the reason for this lack of knowledge is undoubtedly the fact that European researchers -- for the most part -- have been rather reluctant to publish their work in English-language journals. The book concentrates on European research because the basic approach European scholars have taken to studying CPS is very different from one taken by North American researchers. Traditionally, American scholars have been studying CPS in "natural" domains -- physics, reading, writing, and chess playing -- concentrating primarily on exploring novice-expert differences and the acquisition of a complex skill. European scholars, in contrast, have been primarily concerned with problem solving behavior in artificially generated, mostly computerized, complex systems. While the American approach has the advantage of high external validity, the European approach has the advantage of system variables that can be systematically manipulated to reveal the effects of system parameters on CPS behavior. The two approaches are thus best viewed as complementing each other. This volume contains contributions from four European countries -- Sweden, Switzerland, Great Britain, and Germany. As such, it accurately represents the bulk of empirical research on CPS which has been conducted in Europe. An international cooperation started two years ago with the goal of bringing the European research on complex problem solving to the awareness of American scholars. A direct result of that effort, the contributions to this book are both informative and comprehensive.
Forget the IQ tests and tweak those parts of intelligence that matter most to real world success. Sure, having a high IQ is great. But surprisingly, science shows that mental abilities not captured in IQ tests can have the most impact in the real world—attributes like creativity, willpower, emotional intelligence, and intuition. And yes—you can train those skills. In these pages, journalist Garth Sundem draws on interviews with psychology’s top experts and the latest research to show you how. Beyond IQ is a new kind of braintraining guide, one packed with useful, engaging exercises scientifically shown to help you make the most of the brain you've got in the arena that matters most—life!" BEYOND IQ is filled with simple pen-and-paper exercises that will help you: --teach your mind to hear that "eureka" moment of insight --improve your problem-solving skills --use divergent thinking to boost your creativity --retrain your intuition to become more trustworthy --avoid the cognitive "blinkering" that too often comes with expertise --expand your working memory --practice your performance under pressure --improve your pattern-recognition skills --sharpen your emotional intelligence --strengthen your willpower And more!
Problem solving is a central topic for both cognitive psychology and artificial intelligence (AI). Psychology seeks to analyze naturally occur ring problem solving into hypothetical processes, while AI seeks to synthesize problem-solving performance from well-defined processes. Psychology may suggest possible processes to AI and, in turn, AI may suggest plausible hypotheses to psychology. It should be useful for both sides to have some idea of the other's contribution-hence this book, which brings together overviews of psychological and AI re search in major areas of problem solving. At a more general level, this book is intended to be a contribution toward comparative cognitive science. Cognitive science is the study of intelligent systems, whether natural or artificial, and treats both organ isms and computers as types of information-processing systems. Clearly, humans and typical current computers have rather different functional or cognitive architectures. Thus, insights into the role of cognitive ar chitecture in performance may be gained by comparing typical human problem solving with efficient machine problem solving over a range of tasks. Readers may notice that there is little mention of connectionist ap proaches in this volume. This is because, at the time of writing, such approaches have had little or no impact on research at the problem solving level. Should a similar volume be produced in ten years or so, of course, a very different story may need to be told.