Publication

Cost Identification in Finite-horizon Linear Quadratic Gaussian Games

2026

Abstract

This work addresses cost identification in a finite-horizon linear quadratic Gaussian game. We characterize the set of cost parameters that generate a given Nash equilibrium policy and propose a backpropagation algorithm to compute these parameters. A probabilistic error bound is derived in case the cost parameters are identified from finite trajectories. Through numerical and driving simulations, our algorithm identifies the cost parameters that can reproduce the Nash equilibrium policy and trajectory observations.

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2026

Abstract

Official source

Related concepts (19)

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Related publications (1)

Cost Identification in Finite-horizon Linear Quadratic Gaussian Games

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