Abstract
We study a single task allocation problem where each worker connects to some other workers to form a network and the task requester only connects to some of the workers. The goal is to design an allocation mechanism such that each worker is incentivized to invite her neighbours to join the allocation, although they are competing for the task. Moreover, the performance of each worker is uncertain, which is modelled as the quality level of her task execution. The literature has proposed solutions to tackle the uncertainty problem by paying them after verifying their execution. Here, we extend the problem to the network setting. The challenge is that the requester relies on the workers to invite each other to find the best worker, and the performance of each worker is also unknown to the task requester. In this paper, we propose a new mechanism to solve the two challenges at the same time. The mechanism guarantees that inviting more workers and reporting/performing according to her true ability is a dominant strategy for each worker. We believe that the new solution can be widely applied in the digital economy powered by social connections such as crowdsourcing and contests.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Assume that there exists at least one agent whose cost to perform the task is less than q, otherwise we can add a dummy agent d with \(c_d=q\), and the payoff to the dummy agent is always 0 to ensure the social welfare will be non-negative.
References
Chawla, S., Hartline, J.D., Sivan, B.: Optimal crowdsourcing contests. Games Econ. Behav. 113, 80–96 (2019)
Conitzer, V., Vidali, A.: Mechanism design for scheduling with uncertain execution time. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2014, pp. 623–629. AAAI Press (2014)
Dash, R.K., Vytelingum, P., Rogers, A., David, E., Jennings, N.R.: Market-based task allocation mechanisms for limited-capacity suppliers. IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 37(3), 391–405 (2007)
Goel, G., Nikzad, A., Singla, A.: Allocating tasks to workers with matching constraints: truthful mechanisms for crowdsourcing markets. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 279–280 (2014)
Jiang, Y., Zhou, Y., Wang, W.: Task allocation for undependable multiagent systems in social networks. IEEE Trans. Parallel Distrib. Syst. 24(8), 1671–1681 (2012)
Li, B., Hao, D., Gao, H., Zhao, D.: Diffusion auction design. Artif. Intell. 303, 103631 (2022)
Li, B., Hao, D., Zhao, D.: Incentive-compatible diffusion auctions. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, pp. 231–237. ijcai.org (2020)
Li, B., Hao, D., Zhao, D., Zhou, T.: Mechanism design in social networks. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, pp. 586–592. AAAI Press (2017)
Li, Y.M., Shiu, Y.L.: A diffusion mechanism for social advertising over microblogs. Decis. Supp. Syst. 54(1), 9–22 (2012)
Nisan, N., Ronen, A.: Algorithmic mechanism design. Games Econ. Behav. 35(1–2), 166–196 (2001)
Porter, R., Ronen, A., Shoham, Y., Tennenholtz, M.: Fault tolerant mechanism design. Artif. Intell. 172(15), 1783–1799 (2008)
Ramchurn, S.D., Mezzetti, C., Giovannucci, A., Rodriguez-Aguilar, J.A., Dash, R.K., Jennings, N.R.: Trust-based mechanisms for robust and efficient task allocation in the presence of execution uncertainty. J. Artif. Intell. Res. 35, 119–159 (2009)
Shi, H., Zhang, Y., Si, Z., Wang, L., Zhao, D.: Maximal information propagation with budgets. In: ECAI 2020–24th European Conference on Artificial Intelligence, vol. 325, pp. 211–218. IOS Press (2020)
Tang, J.C., Cebrian, M., Giacobe, N.A., Kim, H.W., Kim, T., Wickert, D.B.: Reflecting on the darpa red balloon challenge. Commun. ACM 54(4), 78–85 (2011)
de Weerdt, M.M., Zhang, Y., Klos, T.: Multiagent task allocation in social networks. Auton. Agents Multi-Agent Syst. 25(1), 46–86 (2012)
Wu, X., Huang, D., Sun, Y.-E., Bu, X., Xin, Yu., Huang, H.: An efficient allocation mechanism for crowdsourcing tasks with minimum execution time. In: Huang, D.-S., Hussain, A., Han, K., Gromiha, M.M. (eds.) ICIC 2017. LNCS (LNAI), vol. 10363, pp. 156–167. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63315-2_14
Zhao, D.: Mechanism design powered by social interactions. In: Proceedings of the 20th International Conference on Autonomous Agents and Multi-Agent Systems, pp. 63–67 (2021)
Zhao, D.: Mechanism design powered by social interactions: a call to arms. In: Raedt, L.D. (ed.) Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pp. 5831–5835. International Joint Conferences on Artificial Intelligence Organization (2022), early Career
Zhao, D., Ramchurn, S.D., Jennings, N.R.: Fault tolerant mechanism design for general task allocation. In: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, pp. 323–331. ACM (2016)
Acknowledgement
This work is supported by Science and Technology Commission of Shanghai Municipality (No. 22ZR1442200).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, X., Zhang, Y., Zhao, D. (2023). Task Allocation on Networks with Execution Uncertainty. In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (eds) PRIMA 2022: Principles and Practice of Multi-Agent Systems. PRIMA 2022. Lecture Notes in Computer Science(), vol 13753. Springer, Cham. https://doi.org/10.1007/978-3-031-21203-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-21203-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21202-4
Online ISBN: 978-3-031-21203-1
eBook Packages: Computer ScienceComputer Science (R0)