This games create graphs through different types of evolutionary mechanisms (not necessarily in a biological sense). The nature of their algorithm is described in detail at the linked igraph documentation.

play_citation_age(
n,
growth = 1,
bins = n/7100,
p_pref = (1:(bins + 1))^-3,
directed = TRUE
)

play_forestfire(
n,
p_forward,
p_backward = p_forward,
growth = 1,
directed = TRUE
)

play_growing(n, growth = 1, directed = TRUE, citation = FALSE)

play_barabasi_albert(
n,
power,
growth = 1,
growth_dist = NULL,
use_out = FALSE,
appeal_zero = 1,
directed = TRUE,
method = "psumtree"
)

play_barabasi_albert_aging(
n,
power,
power_age,
growth = 1,
growth_dist = NULL,
bins = 300,
use_out = FALSE,
appeal_zero = 1,
appeal_zero_age = 0,
directed = TRUE,
coefficient = 1,
coefficient_age = 1,
window = NULL
)

## Arguments

n

The number of nodes in the graph.

growth

The number of edges added at each iteration

bins

The number of aging bins

p_pref

The probability that an edge will be made to an age bin.

directed

Should the resulting graph be directed

p_forward, p_backward

Forward and backward burning probability

citation

Should a citation graph be created

power

The power of the preferential attachment

growth_dist

The distribution of the number of added edges at each iteration

use_out

Should outbound edges be used for calculating citation probability

appeal_zero

The appeal value for unconnected nodes

method

The algorithm to use for graph creation. Either 'psumtree', 'psumtree-multiple', or 'bag'

power_age

The aging exponent

appeal_zero_age

The appeal value of nodes without age

coefficient

The coefficient of the degree dependent part of attrictiveness

coefficient_age

The coefficient of the age dependent part of attrictiveness

window

The aging window to take into account when calculating the preferential attraction

## Value

A tbl_graph object

## Functions

• play_citation_age(): Create citation graphs based on a specific age link probability. See igraph::sample_last_cit()

• play_forestfire(): Create graphs by simulating the spead of fire in a forest. See igraph::sample_forestfire()

• play_growing(): Create graphs by adding a fixed number of edges at each iteration. See igraph::sample_growing()

• play_barabasi_albert(): Create graphs based on the Barabasi-Alberts preferential attachment model. See igraph::sample_pa()

• play_barabasi_albert_aging(): Create graphs based on the Barabasi-Alberts preferential attachment model, incoorporating node age preferrence. See igraph::sample_pa_age().

play_traits() and play_citation_type() for an evolutionary algorithm based on different node types
Other graph games: component_games, sampling_games, type_games
plot(play_forestfire(50, 0.5))