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Francesca Di Patti1, Duccio Fanelli1, Francesco Piazza2

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Researchers explored optimal search strategies on complex networks. An ideal mix of local and non-local movements was found to maximize search efficiency, adapting to network structure.

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Area of Science:

  • Network science
  • Complex systems
  • Information theory

Background:

  • Search strategies are crucial in complex networks.
  • Multi-linked networks feature multiple independent sets of links.
  • Understanding optimal search dynamics is an ongoing challenge.

Purpose of the Study:

  • To investigate optimal search strategies on multi-linked networks.
  • To determine how combined local and non-local movements affect search efficiency.
  • To generalize findings to networks with multiple interfering link sets.

Main Methods:

  • Modeling agents performing random walks on graphs.
  • Incorporating non-local hops with a given probability.
  • Analyzing the impact of combined jump rules on search efficiency.
  • Generalizing results for arbitrary numbers of link sets.

Main Results:

  • An optimal combination of local and non-local jumps exists.
  • This optimal strategy maximizes target search efficiency.
  • The optimal strategy is dependent on the network's topology.
  • Results are generalizable to complex multi-linked network structures.

Conclusions:

  • Optimal search on multi-linked networks balances local exploration and global jumps.
  • Network topology critically influences the efficiency of search strategies.
  • The findings provide a framework for designing efficient search algorithms in complex systems.