sparse_bfs

Sparse BFS with Look-ahead and Hybrid Selection

Implements algorithms for analyzing Cayley graphs of permutation groups,
with a focus on the TopSpin puzzle and similar permutation-based combinatorial
puzzles. Provides methods for cycle detection, state space exploration,
bidirectional BFS pathfinding, and finding optimal operation sequences
in permutation groups generated by shift and reverse operations.
Includes C++ implementations of core operations via 'Rcpp' for performance.
Optional GPU acceleration via 'ggmlR' Vulkan backend for batch distance
calculations and parallel state transformations.

Yuri Baramykov

cayleyR

Cayley Graph Analysis for Permutation Puzzles

sparse_bfs function

<dl><dt>start_state</dt>
<dd>Integer vector — starting permutation</dd>
<dt>k</dt>
<dd>Integer — parameter for reverse_prefix operation</dd>
<dt>n_hubs</dt>
<dd>Number of top-degree candidates to keep per level (exploitation)</dd>
<dt>n_random</dt>
<dd>Number of random candidates to keep per level (exploration)</dd>
<dt>max_levels</dt>
<dd>Maximum BFS depth (default 1000)</dd></dl>

Arguments

Sparse BFS with Look-ahead and Hybrid Selection — sparse_bfs

<dl>

<dt>start_state</dt>
<dd>Integer vector — starting permutation</dd>


<dt>k</dt>
<dd>Integer — parameter for reverse_prefix operation</dd>


<dt>n_hubs</dt>
<dd>Number of top-degree candidates to keep per level (exploitation)</dd>


<dt>n_random</dt>
<dd>Number of random candidates to keep per level (exploration)</dd>


<dt>max_levels</dt>
<dd>Maximum BFS depth (default 1000)</dd>

</dl>

sparse_bfs: Sparse BFS with Look-ahead and Hybrid Selection

Description

Usage

Value

Arguments