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Albert N. Link

This book is about inventions and innovation in U.S. Federal Laboratories. The inventions discussed are defined by the technology transfer mechanism known by the term invention disclosures and are innovations that are the output of the technology transfer process. The demonstrated positive relationships in the book's model are the groundwork for suggesting not only a rethinking of the extant empirical research, within the context of a knowledge production function but also a refocusing of U.S. technology policy in support of technology transfer from Federal Laboratories.
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Albert N. Link

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Andrzej Wodecki

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Artificial Intelligence in Management

Self-learning and Autonomous Systems as Key Drivers of Value Creation

Andrzej Wodecki

Autonomous systems are on the frontiers of Artificial Intelligence (AI) research, and they are slowly finding their business applications. Driven mostly by Reinforcement Learning (RL) methods (one of the most difficult, but also the most promising modern AI algorithms), autonomous systems help create self-learning and self-optimising systems, ranging from simple game-playing agents to robots able to efficiently act in completely new environments. Based on in-depth study of more than 100 projects, Andrzej Wodecki explores RL as a key component of modern digital technologies, its real-life applications to activities in a value chain and the ways in which it impacts different industries.
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Andrzej Wodecki

In this chapter we introduce main topics covered in this book, its motivation, and briefly describe the research methodology. We present the scope of each of the proceeding chapters, and comment on the most important bibliographical sources. I forms the ground for the Chapter 1, focused on fundamental concepts of Artificial Intelligence.

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Edited by Mitsuru Kodama

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Edited by Mitsuru Kodama

Illustrating the interdisciplinary implications for research on creativity development, this book focuses on the new concept of ‘knowledge differences’ that arise between people, organizations and various phenomena. It describes how these key differences create boundaries knowledge, a dynamic process that accelerates innovation.
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Edited by Mitsuru Kodama

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Edited by Viktor Dörfler and Marc Stierand

This Handbook offers an insightful journey through the landscape of research methods used to study the phenomenon of creativity. Offering a methodological panorama for the global community of creativity researchers, contributors provide markers and waypoints to better orient scholars and encourage reflection on how one might produce exceptional research on the burgeoning field of creativity.
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Viktor Dörfler and Marc Stierand

This introduction is an attempt to prepare our readers for an exceptional journey into the fascinating landscape of research methods used to study the remarkable phenomenon of creativity. Building on what is already available about research methods on creativity, we explain what we were trying to achieve, how we went about it, and why we are proud of what we have achieved – primarily through the work of our contributors to this handbook. Most of this introduction is dedicated to brief descriptions of the chapters of the book. At the end, we make some suggestions for using this edited volume. Creativity research has significantly matured in recent years, resulting in a wide variety of models and views of creativity (see Runco, 2019 for a recent comprehensive overview). Scholarly interest in creativity has gone mainstream, and dedicated creativity journals such as Journal of Creative Behavior, Creativity Research Journal, Thinking Skills and Creativity, Creativity and Innovation Management, and Psychology of Aesthetics, Creativity, and the Arts are actively competing with more general psychology and management journals to publish the best and most interesting creativity research. In addition, the topic of creativity is becoming popular in a variety of other disciplines, such as biology and neuropsychology (Shiu, 2014).