  One of the main motivations for the use of competitive coevolution systems is
their ability to capitalise on arms races between competing species to evolve
increasingly sophisticated solutions. Such arms races can, however, be hard to
sustain, and it has been shown that the competing species often converge
prematurely to certain classes of behaviours. In this paper, we investigate if
and how novelty search, an evolutionary technique driven by behavioural
novelty, can overcome convergence in coevolution. We propose three methods for
applying novelty search to coevolutionary systems with two species: (i) score
both populations according to behavioural novelty; (ii) score one population
according to novelty, and the other according to fitness; and (iii) score both
populations with a combination of novelty and fitness. We evaluate the methods
in a predator-prey pursuit task. Our results show that novelty-based approaches
can evolve a significantly more diverse set of solutions, when compared to
traditional fitness-based coevolution.
