Tootfinder

This https://arxiv.org/abs/2308.13301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

On Incentivizing Social Information Sharing Through Routing Games
Crowdsourcing services, such as Waze, leverage a mass of mobile users to learn massive point-of-interest (PoI) information while traveling and share it as a public good. Given that crowdsourced users mind their travel costs and possess various preferences over the PoI information along different paths, we formulate the problem as a novel non-atomic multi-path routing game with positive network externalities among users in social information sharing. In the absence of any incentive design, our p…

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff
https://arxiv.org/abs/2505.23124

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
We initiate the study of a repeated principal-agent problem over a finite horizon $T$, where a principal sequentially interacts with $K\geq 2$ types of agents arriving in an adversarial order. At each round, the principal strategically chooses one of the $N$ arms to incentivize for an arriving agent of unknown type. The agent then chooses an arm based on its own utility and the provided incentive, and the principal receives a corresponding reward. The objective is to minimize regret against the…

Chameleon Channels: Measuring YouTube Accounts Repurposed for Deception and Profit
Alejandro Cuevas, Manoel Horta Ribeiro, Nicolas Christin
https://arxiv.org/abs/2507.16045

Chameleon Channels: Measuring YouTube Accounts Repurposed for Deception and Profit
Online content creators spend significant time and effort building their user base through a long, often arduous process, which requires finding the right ``niche'' to cater to. So, what incentive is there for an established content creator known for cat memes to completely reinvent their page channel and start promoting cryptocurrency services or cover electoral news events? And, if they do, do their existing subscribers not notice? We explore this problem of \textit{repurposed channels}, wher…

Optimal Incentive for Regulated Production
Benhao Du, Thomas Treillard, Francois Wang
https://arxiv.org/abs/2506.14286 https://arxiv.…

Optimal Incentive for Regulated Production
This paper explores stochastic control models in the context of decarbonization within the energy market. We study three progressively complex scenarios: (1) a single firm operating with two technologies-one polluting and one clean,(2)two firms model and (3) two firms without any regulatory incentive. For each setting, we formulate the corresponding stochastic control problem and characterize the firms' optimal strategies in terms of investment and production. The analysis highlights the strate…

Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
Benjamin Schiffer, Mark Sellke
https://arxiv.org/abs/2506.01685 h…

Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
In the incentivized exploration model, a principal aims to explore and learn over time by interacting with a sequence of self-interested agents. It has been recently understood that the main challenge in designing incentive-compatible algorithms for this problem is to gather a moderate amount of initial data, after which one can obtain near-optimal regret via posterior sampling. With high-dimensional contexts, however, this \emph{initial exploration} phase requires exponential sample complexity…

Resolving CAP Through Automata-Theoretic Economic Design: A Unified Mathematical Framework for Real-Time Partition-Tolerant Systems
Craig S Wright
https://arxiv.org/abs/2507.02464

Resolving CAP Through Automata-Theoretic Economic Design: A Unified Mathematical Framework for Real-Time Partition-Tolerant Systems
The CAP theorem asserts a trilemma between consistency, availability, and partition tolerance. This paper introduces a rigorous automata-theoretic and economically grounded framework that reframes the CAP trade-off as a constraint optimization problem. We model distributed systems as partition-aware state machines and embed economic incentive layers to stabilize consensus behavior across adversarially partitioned networks. By incorporating game-theoretic mechanisms into the global transition se…