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This paper proposes to use evolutionary computations to determine the parameters of probabilistic finite state machine controllers for swarm robots. The robots are evolved to perform an aggregation task. This… Click to show full abstract
This paper proposes to use evolutionary computations to determine the parameters of probabilistic finite state machine controllers for swarm robots. The robots are evolved to perform an aggregation task. This problem was formulated as an optimization problem and solved by the PSO. Several computer simulations were conducted to investigate the validity of the proposed method. The results obtained in this paper show us that the proposed method is useful for the aggregation problem and the best evolved controllers are feasible as well as interpretable. This would be transferable to real swarm robots problems.
Journal Title: Artificial Life and Robotics
Year Published: 2018
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