Switcher-random-walks: a cognitive-inspired mechanism for network exploration

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 within a subcategory, and, when a subcategory is exhausted, -switching- to a new subcategory. We extended this approach to random-walking on a network (clustering) in combination to jumping (switching) to any node with certain probability and derived its analytical expression based on Markov chains. Results show that this dual mechanism contributes to optimize the exploration of different network models in terms of the mean first passage time. Additionally, this cognitive inspired dual mechanism opens a new framework to better understand and evaluate exploration, propagation and transport phenomena in other complex systems where switching-like phenomena are feasible.