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  • title: What Can Learned Intrinsic Rewards Capture?
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            What Can Learned Intrinsic Rewards Capture?
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            What Can Learned Intrinsic Rewards Capture?

            Jul 12, 2020

            Speakers

            ZZ

            Zeyu Zheng

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            JO

            Junhyuk Oh

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            MH

            Matteo Hessel

            Speaker · 0 followers

            About

            The objective of a reinforcement learning agent is to behave so as to maximise the sum of a suitable scalar function of state: the reward. These rewards are typically given and immutable. In this paper, we instead consider the proposition that the reward function itself can be a good locus of learned knowledge. To investigate this, we propose a scalable meta-gradient framework for learning useful intrinsic reward functions across multiple lifetimes of experience. Through several proof-of-concept…

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            ICML 2020

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            About ICML 2020

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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