The perceptual crossing task has been used to understand social interaction for over a decade. To what extent is the interaction between evolved perceptual crossers truly mutual? To address this question, we undertake a three-pronged examination of the mutuality of simulated social interaction. First, we construct a decoy object that moves at a set amplitude and frequency. This decoy object serves as a benchmark to systematically assess whether the agents can be deceived by non-social oscillatory movement - essentially, whether they mistake the simple, mechanical movement of the decoy for the behavior of another agent. Second, we use agents’ performance with the decoy and agents’ performance with each other to identify convincingly social agents for further analysis. This approach helped us identify that many agents, previously thought to be robust, did not meet our criteria for mutual interaction. However, it also importantly led to the identification of three agents that demonstrate the strongest potential for genuine mutual interaction. Finally, we delve into a detailed investigation of these three agents, focusing on their behavioral patterns and the dynamic strategies they employ.

We revisit the perceptual crossing simulation studies, which are aimed at challenging methodological individualism in the analysis of social cognition by studying multi-agent real-time interactions. To date, all of these simulation studies have reported that it is practically impossible to evolve artificially a robust behavioral strategy without introducing temporal delays into the simulation. Also, all of the studies report on a single strategy: a perpetually crossing agent pair. Here, we systematically report on the evolutionary success of neural circuits on the perceptual crossing task, with and without sensory delay. We also report on two different strategies in the ensemble of successful solutions, only one of which had been discussed in the literature previously.