Titlebook: Advances in Swarm Intelligence; 13th International C Ying Tan,Yuhui Shi,Ben Niu Conference proceedings 2022 Springer Nature Switzerland AG

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Self-organizing Mobile Robots Swarm Movement Control Simulationation may be achieved, due to such parameters of motion, as swarm azimuth angle and velocity of movement may be set only for the master robot, while slave robots follow master one at the pre-determined distance. The flowchart of the swarm control system is worked out, according which all slave robot

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Training Quantized Deep Neural Networks via?Cooperative Coevolutionerations. Most previous quantization approaches are not applicable to this task since they rely on full-precision gradients to update network weights. To fill this gap, in this work we advocate using Evolutionary Algorithms (EAs) to search for the optimal low-bits weights of DNNs. To efficiently sol

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