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Found 7 papers, 2 papers with code
Credit vs. Discount-Based Congestion Pricing: A Comparison Study
Tolling, or congestion pricing, offers a promising traffic management policy for regulating congestion, but has also attracted criticism for placing outsized financial burdens on low-income users.
Catch Me If You Can: Combatting Fraud in Artificial Currency Based Government Benefits Programs
To address the problem of misreporting fraud in artificial currency based benefits programs, we introduce an audit mechanism that induces a two-stage game between an administrator and users.
Online Learning for Equilibrium Pricing in Markets under Incomplete Information
In this incomplete information setting, we consider the online learning problem of learning equilibrium prices over time while jointly optimizing three performance metrics -- unmet demand, cost regret, and payment regret -- pertinent in the context of equilibrium pricing over a horizon of $T$ periods.
Stochastic Online Fisher Markets: Static Pricing Limits and Adaptive Enhancements
However, the efficacy of pricing schemes in achieving an equilibrium outcome in Fisher markets typically relies on complete knowledge of users' budgets and utilities and requires that transactions happen in a static market wherein all users are present simultaneously.
Online Learning for Traffic Routing under Unknown Preferences
at each period, we show that our approach obtains an expected regret and road capacity violation of $O(\sqrt{T})$, where $T$ is the number of periods over which tolls are updated.
Matching with Transfers under Distributional Constraints
To this end, we first consider the setting when the number of institutions (e. g., firms in a labor market) is one and show that equilibrium arrangements exist irrespective of the nature of the constraint structure or the agents' preferences.
Balancing Fairness and Efficiency in Traffic Routing via Interpolated Traffic Assignment
To address the inherent unfairness of SO routing, we study the ${\beta}$-fair SO problem whose goal is to minimize the total travel time while guaranteeing a ${\beta\geq 1}$ level of unfairness, which specifies the maximum possible ratio between the travel times of different users with shared origins and destinations.
