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Ant Colony Optimization (ACO)-inspired Information-Centric Networking (ICN) routing strategies have been proved having good effect to improve network performance. However, the current proposals lack the adjustment policy especially for different iterations, which causes the redundant overhead. For this purpose, this letter proposes an adaptive ACO-driven ICN routing mechanism, which adaptively allocates the number of interest ants for each iteration (i.e., the differentiated allocation) by analyzing the network status. Based on the practical network topology and dataset, we evaluate the proposed mechanism comparing with the cutting-edge baseline, and the results show that the mechanism is more efficient.