Integrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology
Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subscribing to that perspective to varying extent are presented and discussed, including implicit fitness sharing, semantic GP, co-solvability, trace convergence analysis, pattern-guided program synthesis, and behavioral archives of subprograms. The framework involves several concepts that are new to GP, including execution record, combined trace, and search driver, a generalization of objective function. Empirical evidence gathered in several presented experiments clearly demonstrates the usefulness of behavioral approach. The book contains also an extensive discussion of implications of the behavioral perspective for program synthesis and beyond.
Assessing and Diagnosing Speech Therapy Needs in School is a unique text that offers practical guidance in pedagogical diagnosis of speech and communication difficulties within educational settings It outlines theoretical assumptions of the diagnosis process and presents hands-on solutions for pedagogical and speech therapy. Underpinned by theoretical knowledge and written by experienced practitioners, the book equips its readers with tools to understand the diagnostic process and make accurate diagnoses based on each child’s individual circumstances. It starts by clearly distinguishing between pedagogy and speech therapy and outlines issues and theoretical considerations in diagnosing these disorders. To contextualize the theorical observations, it goes on to present case studies, and touches upon crucial topics including readiness to start education, tendency toward aggressive behavior, aphasia and hearing loss. The authors also elaborate on a range of selected diagnostic tools to assess specific difficulties in speech and language therapy. Finally, a list of resources, including games and exercises that can target reading, writing and articulation skills to help children develop, are also featured in the book. Highlighting the importance of practical and theoretical knowledge for those who work with children, this will be a valuable aid for teachers, special educators and speech and language therapists working within school settings. The book will also be of interest to students, teachers and trainee practitioners in the fields of speech therapy and special educational needs.
This book provides a comprehensive overview of the fundamental concepts and principles of microeconomics. It introduces students to the models, assumptions, and empirical applications of modern microeconomics, as well as to the necessary mathematical tools. It covers topics such as economic behavior, consumer theory, theory of the firm, partial and general equilibrium theory, industrial organization, bargaining theory, and Pareto optimality. Students learn not only about economic outcomes at a given point of equilibrium, but also about dynamic economics, which includes both equilibrium and disequilibrium. This book is intended for undergraduate and graduate students in economics and related fields who are interested in the basic theories and applications of microeconomics.
Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subscribing to that perspective to varying extent are presented and discussed, including implicit fitness sharing, semantic GP, co-solvability, trace convergence analysis, pattern-guided program synthesis, and behavioral archives of subprograms. The framework involves several concepts that are new to GP, including execution record, combined trace, and search driver, a generalization of objective function. Empirical evidence gathered in several presented experiments clearly demonstrates the usefulness of behavioral approach. The book contains also an extensive discussion of implications of the behavioral perspective for program synthesis and beyond.
Integrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology
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