  The independent set reconfiguration problem (ISReconf) is the problem of
determining, for given independent sets I_s and I_t of a graph G, whether I_s
can be transformed into I_t by repeatedly applying a prescribed reconfiguration
rule that transforms an independent set to another. As reconfiguration rules
for the ISReconf, the Token Sliding (TS) model and the Token Jumping (TJ) model
are commonly considered. While the TJ model admits the addition of any vertex
(as far as the addition yields an independent set), the TS model admits the
addition of only a neighbor of the removed vertex. It is known that the
complexity status of the ISReconf differs between the TS and TJ models for some
graph classes.
  In this paper, we analyze how changes in reconfiguration rules affect the
computational complexity of reconfiguration problems. To this end, we
generalize the TS and TJ models to a unified reconfiguration rule, called the
k-Jump model, which admits the addition of a vertex within distance k from the
removed vertex. Then, the TS and TJ models are the 1-Jump and D(G)-Jump models,
respectively, where D(G) denotes the diameter of a connected graph G. We give
the following three results: First, we show that the computational complexity
of the ISReconf under the k-Jump model for general graphs is equivalent for all
k >= 3. Second, we present a polynomial-time algorithm to solve the ISReconf
under the 2-Jump model for split graphs. We note that the ISReconf under the
1-Jump (i.e., TS) model is PSPACE-complete for split graphs, and hence the
complexity status of the ISReconf differs between k = 1 and k = 2. Third, we
consider the optimization variant of the ISReconf, which computes the minimum
number of steps of any transformation between Is and It. We prove that this
optimization variant under the k-Jump model is NP-complete for chordal graphs
of diameter at most 2k + 1, for any k >=3.
