A reward-learning framework of knowledge acquisition by Kou Murayama

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【Title】A reward-learning framework of knowledge acquisition: How we can
integrate the concepts of curiosity, interest, and intrinsic-extrinsic
rewards.

【Speaker】 Kou Murayama, Professor
Tübingen University

【Abstract】
Recent years have seen a considerable surge of research on
interest-based engagement, examining how and why people are engaged in
activities without relying on extrinsic rewards. However, the field of
inquiry has been somewhat segregated into three different research
traditions which have been developed relatively independently ---
research on curiosity, interest, and trait curiosity/interest. The
current talk sets out an integrative perspective; the reward-learning
framework of knowledge acquisition. This conceptual framework takes on
the basic premise of existing reward-learning models of information
seeking: that knowledge acquisition serves as an inherent reward, which
reinforces people’s information-seeking behavior through a
reward-learning process. However, the framework reveals how the
knowledge-acquisition process is sustained and boosted over a long
period of time in real-life settings, allowing us to integrate the
different research traditions within reward-learning models. The
framework also characterizes the knowledge-acquisition process with four
distinct features that are not present in the reward-learning process
with extrinsic rewards --- (1) cumulativeness, (2) selectivity, (3)
vulnerability, and (4) under-appreciation. The talk describes some
evidence from our lab supporting these claims.

【Other Information】
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Please contact Hiroaki Hamada, Autonomous Agent Team, Araya Inc. if you have any questions.
Twitter: @HiroTaiyoHamada
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