Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control

We introduce an Implicit Game-Theoretic MPC (IGT-MPC), a decentralized algorithm for two-agent motion planning that uses a learned value function that predicts the game-theoretic interaction outcomes as the terminal cost-to-go function in a model predictive control (MPC) framework, guiding agents to...

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Hauptverfasser:	Kim, Hansung, Zhu, Edward L, Lim, Chang Seok, Borrelli, Francesco
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Multiagent Systems Computer Science - Robotics Computer Science - Systems and Control
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