  Players of coevolutionary games may update not only their strategies but also
their networks of interaction. Based on interpreting the payoff of players as
fitness, dynamic landscape models are proposed. The modeling procedure is
carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use
either birth--death (BD) or death--birth (DB) strategy updating. The main focus
is on using dynamic fitness landscapes as a mathematical model of
coevolutionary game dynamics. Hence, an alternative tool for analyzing
coevolutionary games becomes available, and landscape measures such as
modality, ruggedness and information content can be computed and analyzed. In
addition, fixation properties of the games and quantifiers characterizing the
interaction networks are calculated numerically. Relations are established
between landscape properties expressed by landscape measures and quantifiers of
coevolutionary game dynamics such as fixation probabilities, fixation times and
network properties.
