search_rw: Search network using switcher-random walk process
In memnet: Network Tools for Memory Research

Description Usage Arguments Details Value References Examples

Traverses a network using a switcher-random walk process and records the number of steps required to get from node start to node observe.

1 2	search_rw(adjlist, start, observe, nmax = 1000L, pjump = 0, type = 0L)

`adjlist`	a list containing row indices of nodes adjacent node to the ith node as created by get_adjlist.
`start`	integer vector of length 1 or larger specifying the index of the start node.
`observe`	integer vector of length 1 or larger specifying the target end nodes.
`nmax`	integer specifying the maximum number of steps before search terminates.
`pjump`	numeric specifying the probability of a jump.
`type`	integer controlling network start and jump nodes. For `type = 0` the process selects the start node and any jump nodes proportional to their degree. For `type = 1` the process selects a random node to serve both as the start node and the jump node. For `type = 2` the process selects the start and any jump nodes uniformly at random.

If a node specified in observe has never been visited then the function returns nmax for that node.

Numeric, 3 column matrix containing in each row the start node, the end node, and the (minimum) number of steps it took to reach the end node from the start node.

Wulff, D. U., Hills, T., & Mata, R. (2018, October 29). Structural differences in the semantic networks of younger and older adults. https://doi.org/10.31234/osf.io/s73dp

Goni, J., Martincorena, I., Corominas-Murtra, B., Arrondo, G., Ardanza- Trevijano, S., & Villoslada, P. (2010). Switcher-random-walks: A cognitive- inspired mechanism for network exploration. International Journal of Bifurcation and Chaos, 20(03), 913-922.

# generate watts strogatz graph
network = grow_ws(n = 100, k = 10)

# observe number of steps from node 2 and 6
# to nodes 3, 4, and 5
search_rw(get_adjlist(network), c(2, 6), c(3, 4, 5))

# observe number of steps from node 2 and 6 to nodes 3, 4, and 5
# with high jump probability
search_rw(get_adjlist(network), start = c(2, 6), observe = c(3, 4, 5), pjump = .5)