September 29, 2025Open Access

Maximal entropy random walks and central Markov chains

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Maximal entropy random walks (MERWs) extend to infinite settings, maximizing entropy production.
MERWs are identified as specific instances of central Markov chains, aiding in combinatorial identity derivation.
The study retrieves and extends formulas for binary trees while linking them to the behavior of binary search trees.
Monte Carlo methods based on Knuth's algorithm approximate MERWs and apply to pyramidal growth models.

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This work demonstrates maximal entropy random walks in weighted bratteli diagrams, indicating their link to central Markov chains.

Offret et al. (2025) studied this question.

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