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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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. This will be made on different Cu-FR4-Cu laminate test-structures with a FR4 thickness ranging between 35 to 100 μm. A preliminary assembly process optimization will be performed (e.g., temperature
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