Intrinsically Motivated Learning in Natural and Artificial Systems
Intrinsically Motivated Learning in Natural and Artificial Systems
It has become clear to researchers in
robotics and adaptive behaviour that current approaches are yielding
systems with limited autonomy and capacity for self-improvement. To
learn autonomously and in a cumulative fashion is one of the hallmarks
of intelligence, and we know that higher mammals engage in exploratory
activities that are not directed to pursue goals of immediate relevance
for survival and reproduction but are instead driven by intrinsic
motivations such as curiosity, interest in novel stimuli or surprising
events, and interest in learning new behaviours. The adaptive value of
such intrinsically motivated activities lies in the fact that they allow
the cumulative acquisition of knowledge and skills that can be used
later to accomplish ļ¬tness-enhancing goals. Intrinsic motivations
continue during adulthood, and in humans they underlie lifelong
learning, artistic creativity, and scientific discovery, while they are
also the basis for processes that strongly affect human well-being, such
as the sense of competence, self-determination, and self-esteem.
This book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations.
The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.
The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.
Ebook format: PDFThis book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations.
The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.
The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.
Ebook page: 440
File size: 8.00 MB
$40.00
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