Standard

Reputation systems for human-computer environments. / Kolonin, Anton.

2019. 211-215 Работа представлена на 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019, Orlando, Соединенные Штаты Америки.

Результаты исследований: Материалы конференцийматериалыРецензирование

Harvard

Kolonin, A 2019, 'Reputation systems for human-computer environments', Работа представлена на 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019, Orlando, Соединенные Штаты Америки, 12.03.2019 - 15.03.2019 стр. 211-215.

APA

Kolonin, A. (2019). Reputation systems for human-computer environments. 211-215. Работа представлена на 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019, Orlando, Соединенные Штаты Америки.

Vancouver

Kolonin A. Reputation systems for human-computer environments. 2019. Работа представлена на 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019, Orlando, Соединенные Штаты Америки.

Author

Kolonin, Anton. / Reputation systems for human-computer environments. Работа представлена на 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019, Orlando, Соединенные Штаты Америки.5 стр.

BibTeX

@conference{6fc264bfa1be456f9517beb337038f58,
title = "Reputation systems for human-computer environments",
abstract = "Understanding the principles of consensus in communities and finding ways to find solutions to the optimal community as a whole becomes crucial as the speeds and scales of interaction in modern distributed systems increase. Such systems can be both socially-information computer networks that unite the masses of people, and multi-agent computing platforms, including peer-to-peer systems such as blockchains, operating on the basis of distributed ledger. Finally, it is now becoming possible for hybrid ecosystems to emerge, which include both humans and computer systems using artificial intelligence. We propose a new form of consensus for such systems, based on the reputation of the participants, calculated according to the principle of {"}fluid democracy{"}. We expect that such a system will be more resistant to social engineering and reputation manipulation than the existing systems. In this article, we discuss the basic principles and options for implementing such a system, and also present preliminary practical results.",
keywords = "Collective Intelligence, Consensus, Distributed Systems, Liquid Democracy, Peer-to-Peer, Reputation, Social Computing",
author = "Anton Kolonin",
year = "2019",
month = jan,
day = "1",
language = "English",
pages = "211--215",
note = "10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019 ; Conference date: 12-03-2019 Through 15-03-2019",

}

RIS

TY - CONF

T1 - Reputation systems for human-computer environments

AU - Kolonin, Anton

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Understanding the principles of consensus in communities and finding ways to find solutions to the optimal community as a whole becomes crucial as the speeds and scales of interaction in modern distributed systems increase. Such systems can be both socially-information computer networks that unite the masses of people, and multi-agent computing platforms, including peer-to-peer systems such as blockchains, operating on the basis of distributed ledger. Finally, it is now becoming possible for hybrid ecosystems to emerge, which include both humans and computer systems using artificial intelligence. We propose a new form of consensus for such systems, based on the reputation of the participants, calculated according to the principle of "fluid democracy". We expect that such a system will be more resistant to social engineering and reputation manipulation than the existing systems. In this article, we discuss the basic principles and options for implementing such a system, and also present preliminary practical results.

AB - Understanding the principles of consensus in communities and finding ways to find solutions to the optimal community as a whole becomes crucial as the speeds and scales of interaction in modern distributed systems increase. Such systems can be both socially-information computer networks that unite the masses of people, and multi-agent computing platforms, including peer-to-peer systems such as blockchains, operating on the basis of distributed ledger. Finally, it is now becoming possible for hybrid ecosystems to emerge, which include both humans and computer systems using artificial intelligence. We propose a new form of consensus for such systems, based on the reputation of the participants, calculated according to the principle of "fluid democracy". We expect that such a system will be more resistant to social engineering and reputation manipulation than the existing systems. In this article, we discuss the basic principles and options for implementing such a system, and also present preliminary practical results.

KW - Collective Intelligence

KW - Consensus

KW - Distributed Systems

KW - Liquid Democracy

KW - Peer-to-Peer

KW - Reputation

KW - Social Computing

UR - http://www.scopus.com/inward/record.url?scp=85066028941&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85066028941

SP - 211

EP - 215

T2 - 10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019

Y2 - 12 March 2019 through 15 March 2019

ER -

ID: 20051792