Intrinsically motivated machines

Children seem intrinsically motivated to manipulate, to explore, to test, to learn and they look for activities and situations that provide such learning opportunities. Inspired by research in developmental psychology and neuroscience, some researchers have started to address the problem of designing intrinsic motivation systems. A robot controlled by such systems is able to autonomously explore its environment not to fulfill predefined tasks but driven by an incentive to search for situations where learning happens efficiently. In this paper, we present the origins of these intrinsically motivated machines, our own research in this novel field and we argue that intrinsic motivation might be a crucial step towards machines capable of life-long learning and open-ended development.


Editor(s):
Pfeifer, Rolf
Bongard, Josh
Iida, Fumiya
Lungarella, Max
Published in:
50 Years of AI, Festschrift, 304–315
Year:
2007
Publisher:
Springer Verlag
ISBN:
978-3-540-77295-8
Laboratories:




 Record created 2008-01-23, last modified 2018-03-18

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