  Recently, strategic games inspired by Schelling's influential model of
residential segregation have been studied in the TCS and AI literature. In
these games, agents of k different types occupy the nodes of a network topology
aiming to maximize their utility, which is a function of the fraction of
same-type agents they are adjacent to in the network. As such, the agents
exhibit similarity seeking strategic behavior. In this paper, we introduce a
class of strategic jump games in which the agents are diversity-seeking: The
utility of an agent is defined as the fraction of its neighbors that are of
different type than itself. We show that in general it is computationally hard
to determine the existence of an equilibrium in such games. However, when the
network is a tree, diversity-seeking jump games always admit an equilibrium
assignment. For regular graphs and spider graphs with a single empty node, we
prove a stronger result: The game is potential, that is, the improving response
dynamics always converge to an equilibrium from any initial placement of the
agents. We also show (nearly tight) bounds on the price of anarchy and price of
stability in terms of the social welfare (the total utility of the agents).
