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Found 11 papers, 0 papers with code
Incentive-Compatible Vertiport Reservation in Advanced Air Mobility: An Auction-Based Approach
The rise of advanced air mobility (AAM) is expected to become a multibillion-dollar industry in the near future.
Dynamic Tolling in Arc-based Traffic Assignment Models
We prove that our adaptive learning and marginal pricing dynamics converge to a neighborhood of the socially optimal loads and tolls.
Markov $α$-Potential Games
In this new framework, Markov games are shown to be Markov $\alpha$-potential games, and the existence of an associated $\alpha$-potential function is established.
Arc-based Traffic Assignment: Equilibrium Characterization and Learning
Arc-based traffic assignment models (TAMs) are a popular framework for modeling traffic network congestion generated by self-interested travelers who sequentially select arcs based on their perceived latency on the network.
Follower Agnostic Methods for Stackelberg Games
In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner.
Competing Bandits in Time Varying Matching Markets
We study the problem of online learning in two-sided non-stationary matching markets, where the objective is to converge to a stable match.
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets
We study the problem of online learning in competitive settings in the context of two-sided matching markets.
Independent and Decentralized Learning in Markov Potential Games
We propose a multi-agent reinforcement learning dynamics, and analyze its convergence in infinite-horizon discounted Markov potential games.
Dynamic Tolling for Inducing Socially Optimal Traffic Loads
How to design tolls that induce socially optimal traffic loads with dynamically arriving travelers who make selfish routing decisions?
Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization
Min-max optimization is emerging as a key framework for analyzing problems of robustness to strategically and adversarially generated data.
Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Dendrite Suppression with Li Metal Anode
We predict over 20 mechanically anisotropic interfaces between Li metal and 6 solid electrolytes which can be used to suppress dendrite growth.
