TY - GEN

T1 - Consensus in equilibrium

T2 - 23rd International Conference on Principles of Distributed Systems, OPODIS 2019

AU - Harel, Itay

AU - Jacob-Fanani, Amit

AU - Sulamy, Moshe

AU - Afek, Yehuda

N1 - Publisher Copyright:
© Itay Harel, Amit Jacob-Fanani, Moshe Sulamy, and Yehuda Afek; licensed under Creative Commons License CC-BY 23rd International Conference on Principles of Distributed Systems (OPODIS 2019).

PY - 2020/2

Y1 - 2020/2

N2 - Is there an equilibrium for distributed consensus when all agents except one collude to steer the decision value towards their preference? If an equilibrium exists, then an n − 1 size coalition cannot do better by deviating from the algorithm, even if it prefers a different decision value. We show that an equilibrium exists under this condition only if the number of agents in the network is odd and the decision is binary (among two possible input values). That is, in this framework we provide a separation between binary and multi-valued consensus. Moreover, the input and output distribution must be uniform, regardless of the communication model (synchronous or asynchronous). Furthermore, we define a new problem - Resilient Input Sharing (RIS), and use it to find an iff condition for the (n − 1)-resilient equilibrium for deterministic binary consensus, essentially showing that an equilibrium for deterministic consensus is equivalent to each agent learning all the other inputs in some strong sense. Finally, we note that (n − 2)-resilient equilibrium for binary consensus is possible for any n. The case of (n − 2)-resilient equilibrium for multi-valued consensus is left open.

AB - Is there an equilibrium for distributed consensus when all agents except one collude to steer the decision value towards their preference? If an equilibrium exists, then an n − 1 size coalition cannot do better by deviating from the algorithm, even if it prefers a different decision value. We show that an equilibrium exists under this condition only if the number of agents in the network is odd and the decision is binary (among two possible input values). That is, in this framework we provide a separation between binary and multi-valued consensus. Moreover, the input and output distribution must be uniform, regardless of the communication model (synchronous or asynchronous). Furthermore, we define a new problem - Resilient Input Sharing (RIS), and use it to find an iff condition for the (n − 1)-resilient equilibrium for deterministic binary consensus, essentially showing that an equilibrium for deterministic consensus is equivalent to each agent learning all the other inputs in some strong sense. Finally, we note that (n − 2)-resilient equilibrium for binary consensus is possible for any n. The case of (n − 2)-resilient equilibrium for multi-valued consensus is left open.

KW - Consensus

KW - Distributed computing

KW - Game theory

KW - Rational agents

UR - http://www.scopus.com/inward/record.url?scp=85081172557&partnerID=8YFLogxK

U2 - 10.4230/LIPIcs.OPODIS.2019.20

DO - 10.4230/LIPIcs.OPODIS.2019.20

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85081172557

T3 - Leibniz International Proceedings in Informatics, LIPIcs

BT - 23rd International Conference on Principles of Distributed Systems, OPODIS 2019

A2 - Felber, Pascal

A2 - Friedman, Roy

A2 - Gilbert, Seth

A2 - Miller, Avery

PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing

Y2 - 17 December 2019 through 19 December 2019

ER -