Combinatorial Civic Crowdfunding with Budgeted Agents: Welfare Optimality at Equilibrium and Optimal Deviation

Abstract

Civic Crowdfunding (CC) uses the ``power of the crowd" to garner contributions towards public projects. As these projects are non-excludable, agents may prefer to ``free-ride," resulting in the project not being funded. Researchers introduce refunds for single project CC to incentivize agents to contribute, guaranteeing the project's funding. These funding guarantees are applicable only when agents have an unlimited budget. This paper focuses on a combinatorial setting, where multiple projects are available for CC and agents have a limited budget. We study specific conditions where funding can be guaranteed. Naturally, funding the optimal social welfare subset of projects is desirable when every available project cannot be funded due to budget restrictions. We prove the impossibility of achieving optimal welfare at equilibrium for any monotone refund scheme. Further, given the contributions of other agents, we prove that it is NP-Hard for an agent to determine its optimal strategy. That is, while profitable deviations may exist for agents instead of funding the optimal welfare subset, it is computationally hard for an agent to find its optimal deviation. Consequently, we study different heuristics agents can use to contribute to the projects in practice. We demonstrate the heuristics' performance as the average-case trade-off between the welfare obtained and an agent's utility through simulations.

Cite

Text

Damle et al. "Combinatorial Civic Crowdfunding with Budgeted Agents: Welfare Optimality at Equilibrium and Optimal Deviation." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I5.25693

Markdown

[Damle et al. "Combinatorial Civic Crowdfunding with Budgeted Agents: Welfare Optimality at Equilibrium and Optimal Deviation." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/damle2023aaai-combinatorial/) doi:10.1609/AAAI.V37I5.25693

BibTeX

@inproceedings{damle2023aaai-combinatorial,
  title     = {{Combinatorial Civic Crowdfunding with Budgeted Agents: Welfare Optimality at Equilibrium and Optimal Deviation}},
  author    = {Damle, Sankarshan and Padala, Manisha and Gujar, Sujit},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {5582-5590},
  doi       = {10.1609/AAAI.V37I5.25693},
  url       = {https://mlanthology.org/aaai/2023/damle2023aaai-combinatorial/}
}