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Learning in Inverse Games: Tractable Training with Probabilistic Guarantees
Arghya Mallick, Reza Rahimi Baghbadorani, Peyman Mohajerin Esfahani +1
Inverse game theory seeks to learn agents' unknown objectives from observed equilibrium behavior. Existing residual-based approaches can lead to non-convex problems and need not en…
User-centric Vehicle-to-Grid Optimization with an Input Convex Neural Network-based Battery Degradation Model
Arghya Mallick, Georgios Pantazis, Mohammad Khosravi +2
We propose a data-driven, user-centric vehicle-to-grid (V2G) methodology based on multi-objective optimization to balance battery degradation and V2G revenue according to EV user p…
A User-centric Game for Balancing V2G Benefits with Battery Degradation of Electric Vehicles
Arghya Mallick, Georgios Pantazis, Peyman Mohajerin Esfahani +1
We present a novel user-centric vehicle-to-grid (V2G) framework that enables electric vehicle (EV) users to balance the trade-off between financial benefits from V2G and battery he…