Distributed Stackelberg Strategies in State-Based Potential Games for Autonomous Decentralized Learning Manufacturing Systems
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DOI: 10.1109/tsmc.2025.3602958
Abstract: This article presents a novel game-theoretical (GT) framework, distributed Stackelberg strategies in state-based potential games (DS2-SbPGs), for autonomous multiobjective optimization in decentralized manufacturing systems. Existing approaches, including multiagent reinforcement learning (MARL) and native SbPG, struggle… read more here.
Keywords: strategies state; ds2 sbpg; distributed stackelberg; potential games ... See more keywords