Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. / Lesniak, Kacper Kenji; Maistro, Maria.

2022 IEEE Conference on Games, CoG 2022. IEEE Computer Society Press, 2022. p. 64-71 (IEEE Conference on Computatonal Intelligence and Games, CIG, Vol. 2022-August).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Lesniak, KK & Maistro, M 2022, Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. in 2022 IEEE Conference on Games, CoG 2022. IEEE Computer Society Press, IEEE Conference on Computatonal Intelligence and Games, CIG, vol. 2022-August, pp. 64-71, 2022 IEEE Conference on Games, CoG 2022, Beijing, China, 21/08/2022. https://doi.org/10.1109/CoG51982.2022.9893597

APA

Lesniak, K. K., & Maistro, M. (2022). Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. In 2022 IEEE Conference on Games, CoG 2022 (pp. 64-71). IEEE Computer Society Press. IEEE Conference on Computatonal Intelligence and Games, CIG Vol. 2022-August https://doi.org/10.1109/CoG51982.2022.9893597

Vancouver

Lesniak KK, Maistro M. Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. In 2022 IEEE Conference on Games, CoG 2022. IEEE Computer Society Press. 2022. p. 64-71. (IEEE Conference on Computatonal Intelligence and Games, CIG, Vol. 2022-August). https://doi.org/10.1109/CoG51982.2022.9893597

Author

Lesniak, Kacper Kenji ; Maistro, Maria. / Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game. 2022 IEEE Conference on Games, CoG 2022. IEEE Computer Society Press, 2022. pp. 64-71 (IEEE Conference on Computatonal Intelligence and Games, CIG, Vol. 2022-August).

Bibtex

@inproceedings{02bb59063d234815883dd12f158578f5,
title = "Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game",
abstract = "This paper presents a new use case for continuous crowdsourcing, where multiple players collectively control a single character in a video game. Similar approaches have already been proposed, but they suffer from certain limitations: (1) they simply consider static time frames to group real-time inputs from multiple players; (2) then they aggregate inputs with simple majority vote, i.e., each player is uniformly weighted. We present a continuous crowdsourcing multiplayer game equipped with our Crowdsourcing Controller. The Crowdsourcing Controller addresses the above-mentioned limitations: (1) our Dynamic Input Frame approach groups incoming players' input in real-time by dynamically adjusting the frame length; (2) our Continuous Reliability System estimates players' skills by assigning them a reliability score, which is later used in a weighted majority vote to aggregate the final output command. We evaluated our Crowdsourcing Controller offline with simulated players and online with real players. Offline and online experiments show that both components of our Crowdsourcing Controller lead to higher game scores, i.e., longer playing time. Moreover, the Crowdsourcing Controller is able to correctly estimate and update players' reliability scores. ",
keywords = "Crowdsourcing, Multiplayer, Reliability system",
author = "Lesniak, {Kacper Kenji} and Maria Maistro",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Conference on Games, CoG 2022 ; Conference date: 21-08-2022 Through 24-08-2022",
year = "2022",
doi = "10.1109/CoG51982.2022.9893597",
language = "English",
series = "IEEE Conference on Computatonal Intelligence and Games, CIG",
pages = "64--71",
booktitle = "2022 IEEE Conference on Games, CoG 2022",
publisher = "IEEE Computer Society Press",
address = "United States",

}

RIS

TY - GEN

T1 - Crowdsourcing Controller - Utilizing Reliable Agents in a Multiplayer Game

AU - Lesniak, Kacper Kenji

AU - Maistro, Maria

N1 - Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - This paper presents a new use case for continuous crowdsourcing, where multiple players collectively control a single character in a video game. Similar approaches have already been proposed, but they suffer from certain limitations: (1) they simply consider static time frames to group real-time inputs from multiple players; (2) then they aggregate inputs with simple majority vote, i.e., each player is uniformly weighted. We present a continuous crowdsourcing multiplayer game equipped with our Crowdsourcing Controller. The Crowdsourcing Controller addresses the above-mentioned limitations: (1) our Dynamic Input Frame approach groups incoming players' input in real-time by dynamically adjusting the frame length; (2) our Continuous Reliability System estimates players' skills by assigning them a reliability score, which is later used in a weighted majority vote to aggregate the final output command. We evaluated our Crowdsourcing Controller offline with simulated players and online with real players. Offline and online experiments show that both components of our Crowdsourcing Controller lead to higher game scores, i.e., longer playing time. Moreover, the Crowdsourcing Controller is able to correctly estimate and update players' reliability scores.

AB - This paper presents a new use case for continuous crowdsourcing, where multiple players collectively control a single character in a video game. Similar approaches have already been proposed, but they suffer from certain limitations: (1) they simply consider static time frames to group real-time inputs from multiple players; (2) then they aggregate inputs with simple majority vote, i.e., each player is uniformly weighted. We present a continuous crowdsourcing multiplayer game equipped with our Crowdsourcing Controller. The Crowdsourcing Controller addresses the above-mentioned limitations: (1) our Dynamic Input Frame approach groups incoming players' input in real-time by dynamically adjusting the frame length; (2) our Continuous Reliability System estimates players' skills by assigning them a reliability score, which is later used in a weighted majority vote to aggregate the final output command. We evaluated our Crowdsourcing Controller offline with simulated players and online with real players. Offline and online experiments show that both components of our Crowdsourcing Controller lead to higher game scores, i.e., longer playing time. Moreover, the Crowdsourcing Controller is able to correctly estimate and update players' reliability scores.

KW - Crowdsourcing

KW - Multiplayer

KW - Reliability system

U2 - 10.1109/CoG51982.2022.9893597

DO - 10.1109/CoG51982.2022.9893597

M3 - Article in proceedings

AN - SCOPUS:85139148196

T3 - IEEE Conference on Computatonal Intelligence and Games, CIG

SP - 64

EP - 71

BT - 2022 IEEE Conference on Games, CoG 2022

PB - IEEE Computer Society Press

T2 - 2022 IEEE Conference on Games, CoG 2022

Y2 - 21 August 2022 through 24 August 2022

ER -

ID: 344439299