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The Cartographer
Settling the Reward Hypothesis
December 20, 2022 Β· Declared Dead Β· π International Conference on Machine Learning
"No code URL or promise found in abstract"
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Authors
Michael Bowling, John D. Martin, David Abel, Will Dabney
arXiv ID
2212.10420
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LG,
math.ST
Citations
44
Venue
International Conference on Machine Learning
Last Checked
6 months ago
Abstract
The reward hypothesis posits that, "all of what we mean by goals and purposes can be well thought of as maximization of the expected value of the cumulative sum of a received scalar signal (reward)." We aim to fully settle this hypothesis. This will not conclude with a simple affirmation or refutation, but rather specify completely the implicit requirements on goals and purposes under which the hypothesis holds.
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