Designing Preferences, Beliefs, and Identities for Artificial Intelligence

Authors

  • Vincent Conitzer Duke University

DOI:

https://doi.org/10.1609/aaai.v33i01.33019755

Abstract

Research in artificial intelligence, as well as in economics and other related fields, generally proceeds from the premise that each agent has a well-defined identity, well-defined preferences over outcomes, and well-defined beliefs about the world. However, as we design AI systems, we in fact need to specify where the boundaries between one agent and another in the system lie, what objective functions these agents aim to maximize, and to some extent even what belief formation processes they use.

The premise of this paper is that as AI is being broadly deployed in the world, we need well-founded theories of, and methodologies and algorithms for, how to design preferences, identities, and beliefs. This paper lays out an approach to address these problems from a rigorous foundation in decision theory, game theory, social choice theory, and the algorithmic and computational aspects of these fields.

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Published

2019-07-17

How to Cite

Conitzer, V. (2019). Designing Preferences, Beliefs, and Identities for Artificial Intelligence. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9755-9759. https://doi.org/10.1609/aaai.v33i01.33019755

Issue

Section

Senior Member Presentation Track: Blue Sky Papers