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Computer Science > Artificial Intelligence

arXiv:1507.01986 (cs)
[Submitted on 7 Jul 2015]

Title:Toward Idealized Decision Theory

Authors:Nate Soares, Benja Fallenstein
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Abstract: This paper motivates the study of decision theory as necessary for aligning smarter-than-human artificial systems with human interests. We discuss the shortcomings of two standard formulations of decision theory, and demonstrate that they cannot be used to describe an idealized decision procedure suitable for approximation by artificial systems. We then explore the notions of policy selection and logical counterfactuals, two recent insights into decision theory that point the way toward promising paths for future research.
Comments: This is an extended version of a paper accepted to AGI-2015
Subjects: Artificial Intelligence (cs.AI)
Report number: 2014-7
Cite as: arXiv:1507.01986 [cs.AI]
  (or arXiv:1507.01986v1 [cs.AI] for this version)

Submission history

From: Nathaniel Soares [view email]
[v1] Tue, 7 Jul 2015 23:06:59 UTC (165 KB)
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