Switcher-random-walks: a cognitive-inspired mechanism for network exploration
Joaqu\'in Go\~ni, I\~nigo Martincorena, Bernat Corominas-Murtra,, Gonzalo Arrondo, Sergio Ardanza-Trevijano, Pablo Villoslada

TL;DR
This paper introduces a dual mechanism combining random walks and switching to improve network exploration, inspired by cognitive processes in semantic memory, and provides analytical insights into its efficiency.
Contribution
It proposes a novel cognitive-inspired exploration mechanism using switcher-random-walks, combining clustering and switching, with analytical expressions for network traversal efficiency.
Findings
Dual mechanism optimizes network exploration in terms of mean first passage time
Analytical expressions derived for Markov chain-based exploration
Framework applicable to complex systems with switching phenomena
Abstract
Semantic memory is the subsystem of human memory that stores knowledge of concepts or meanings, as opposed to life specific experiences. The organization of concepts within semantic memory can be understood as a semantic network, where the concepts (nodes) are associated (linked) to others depending on perceptions, similarities, etc. Lexical access is the complementary part of this system and allows the retrieval of such organized knowledge. While conceptual information is stored under certain underlying organization (and thus gives rise to a specific topology), it is crucial to have an accurate access to any of the information units, e.g. the concepts, for efficiently retrieving semantic information for real-time needings. An example of an information retrieval process occurs in verbal fluency tasks, and it is known to involve two different mechanisms: -clustering-, or generating words…
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