Abstract
To build a creative agent that never stops generating non-trivial & novel & surprising data, we need two learning modules: (1) an adaptive predictor or compressor or model of the growing data history as the agent is interacting with its environment, and (2) a general reinforcement learner. The LEARNING PROGRESS of (1) is the FUN or intrinsic reward of (2). That is, (2) is motivated to invent interesting things that (1) does not yet know but can easily learn.
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© 2010 Springer-Verlag Berlin Heidelberg
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Schmidhuber, J. (2010). Formal Theory of Fun and Creativity. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010. Lecture Notes in Computer Science(), vol 6321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15880-3_6
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DOI: https://doi.org/10.1007/978-3-642-15880-3_6
Publisher Name: Springer, Berlin, Heidelberg
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