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 inter est 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 fitness-enhanc ing
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.
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