Influence Maximization is the task of selecting optimal nodes maximising the
influence spread in social networks. This study proposes a Discretized
Quantum-based Salp Swarm Algorithm (DQSSA) for optimizing influence diffusion
in social networks. By discretizing meta-heuristic algorithms and infusing them
with quantum-inspired enhancements, we address issues like premature
convergence and low efficacy. The proposed method, guided by quantum
principles, offers a promising solution for Influence Maximisation. Experiments
on four real-world datasets reveal DQSSA's superior performance as compared to
established cutting-edge algorithms.Comment: AAAI Conference on Artificial Intelligence 202