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Multi-Agent Temporal Logic Planning via Penalty Functions and Block-Coordinate Optimization
arXiv:2602.17434v2 Announce Type: replace Abstract: Multi-agent planning under Signal Temporal Logic (STL) is often hindered by collaborative tasks that lead to computational challenges due to the inherent high dimensionality of the problem, preventing scalable synthesis with satisfaction guarantees. To address this, we formulate STL planning as an optimization program under multi-agent STL constraints and introduce a penalty-based unconstrained relaxation that can be efficiently solved via...