Excited random walks with Markovian cookie stacks
Elena Kosygina, Jonathon Peterson

TL;DR
This paper studies a one-dimensional excited random walk with Markovian cookie stacks, revealing different behaviors in critical and non-critical regimes, including transience, recurrence, ballisticity, and limit laws, generalizing previous periodic models.
Contribution
It introduces a Markovian environment for excited random walks, providing new criteria for recurrence, transience, and limit laws, extending the understanding beyond periodic cookie stacks.
Findings
Non-critical regime: walk is transient with non-zero speed and obeys CLT.
Critical regime: diverse behaviors with specific recurrence/transience conditions.
Results generalize and improve upon previous models with periodic cookie stacks.
Abstract
We consider a nearest-neighbor random walk on whose probability to jump to the right from site depends not only on but also on the number of prior visits to . The collection is sometimes called the "cookie environment" due to the following informal interpretation. Upon each visit to a site the walker eats a cookie from the cookie stack at that site and chooses the transition probabilities according to the "strength" of the cookie eaten. We assume that the cookie stacks are i.i.d. and that the cookie "strengths" within the stack at site follow a finite state Markov chain. Thus, the environment at each site is dynamic, but it evolves according to the local time of the walk at each site rather than the original random walk time. The model admits two different regimes, critical…
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