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https://dx.doi.org/10.48550/ar...
Article . 2021
License: CC BY
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Game-Theoretic Models of Moral and Other-Regarding Agents (extended abstract)

Authors: Gabriel Istrate;

Game-Theoretic Models of Moral and Other-Regarding Agents (extended abstract)

Abstract

We investigate Kantian equilibria in finite normal form games, a class of non-Nashian, morally motivated courses of action that was recently proposed in the economics literature. We highlight a number of problems with such equilibria, including computational intractability, a high price of miscoordination, and problematic extension to general normal form games. We give such a generalization based on concept of program equilibria, and point out that that a practically relevant generalization may not exist. To remedy this we propose some general, intuitive, computationally tractable, other-regarding equilibria that are special cases Kantian equilibria, as well as a class of courses of action that interpolates between purely self-regarding and Kantian behavior.

In Proceedings TARK 2021, arXiv:2106.10886. This is the extended abstract that appears in the Proceedings of TARK 2021. A longer, more complete, version of the paper is available as preprint arXiv:2012.09759

Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Computer Science and Game Theory, Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems, Computer Science - Social and Information Networks, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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