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Understanding the mechanism of intelligence in human beings and animals is one of the most important approaches to developing intelligent robot systems. Since the mechanisms of such real-life intelligent systems are so complex, such as the physical interactions between agents and their environment and the social interactions between agents, comprehension and knowledge in many peripheral fields such as cognitive science, developmental psychology, brain science, evolutionary biology, and robotics. Discussions from an interdisciplinary aspect are very important for implementing this approach, but such collaborative research is time-consuming and labor-intensive, and it is difficult to obtain fruitful results from such research because the basis of experiments is very different in each research field. In the social science field, for example, several multi-agent simulation systems have been proposed for modeling factors such as social interactions and language evolution, whereas robotics researchers often use dynamics and sensor simulators. However, there is no integrated system that uses both physical simulations and social communication simulations.
Therefore, we have been developing a simulator environment called SIGVerse, which is a simulator that combines dynamics, perception, and communication simulations for synthetic approaches to research into the genesis of social intelligence. In this paper, we introduce SIGVerse, its example application and perspectives.