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The Role of A-priori Information in Networks of Rational Agents

Authors Yehuda Afek, Shaked Rafaeli, Moshe Sulamy

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ACM Subject Classification
  • Theory of computation → Distributed computing models
Keywords
  • rational agents
  • distributed game theory
  • coloring
  • knowledge sharing

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Abstract

Until now, distributed algorithms for rational agents have assumed a-priori knowledge of n, the size of the network. This assumption is challenged here by proving how much a-priori knowledge is necessary for equilibrium in different distributed computing problems. Duplication - pretending to be more than one agent - is the main tool used by agents to deviate and increase their utility when not enough knowledge about n is given.
We begin by proving that when no information on n is given, equilibrium is impossible for both Coloring and Knowledge Sharing. We then provide new algorithms for both problems when n is a-priori known to all agents. However, what if agents have partial knowledge about n? We provide tight upper and lower bounds that must be a-priori known on n for equilibrium to be possible in Leader Election, Knowledge Sharing, Coloring, Partition and Orientation.

Cite As Get BibTex

Yehuda Afek, Shaked Rafaeli, and Moshe Sulamy. The Role of A-priori Information in Networks of Rational Agents. In 32nd International Symposium on Distributed Computing (DISC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 121, pp. 5:1-5:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.DISC.2018.5

Author Details

Yehuda Afek
  • Tel-Aviv University, Tel-Aviv, Israel
Shaked Rafaeli
  • Tel-Aviv University, Tel-Aviv, Israel
Moshe Sulamy
  • Tel-Aviv University, Tel-Aviv, Israel

Funding

This research was supported by the Israel Science Foundation (grant 1386/11).

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