The Elephant random walk with gradually increasing memory
Allan Gut, Ulrich Stadtm\"uller

TL;DR
This paper investigates the behavior of the Elephant random walk when the memory of past steps increases gradually over time, extending previous models that had fixed or finite memory, and explores related delayed-memory variants.
Contribution
It introduces and analyzes a new model of ERW with gradually increasing memory, providing insights into its properties and phase transitions.
Findings
Identifies different regimes depending on the rate of memory increase
Shows phase transition behavior in the walk's properties
Provides theoretical results on ERW with delayed memory
Abstract
In the simple random walk the steps are independent, viz., the walker has no memory. In contrast, in the Elephant random walk(ERW), which was introduced by Schuetz and Trimper in 2004, the next step always depends on the whole path so far. Various authors have studied further properties of the ERW. In an earlier paper we studied the case when the Elephant remembers only a finite part of the first or last steps. In both cases there was no separation into two different regimes as in the classical ERW. We also posed the question about what happens if she remembers a gradually increasing past. This paper will give some answers to that question. We also discuss related questions for ERW:s with delays.
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Taxonomy
TopicsStochastic processes and statistical mechanics · DNA and Biological Computing · Mathematical Dynamics and Fractals
