Designing Naturalistic Simulations for Evolving AGI Species
Christian Hahm · 2022
This paper identifies basic principles for designing and creating evolutionary simulations in the context of general-purpose AI (AGI). It is argued that evolutionary simulations which employ certain nature-inspired principles can be used to evolve increasingly intelligent AGI species. AGI frameworks are particularly suited for evolutionary experiments involving embodiment since they can operate arbitrary evolved bodies. Once a designer manually defines a simulation’s initial conditions, each run is an automated exploration of a novel subset of species. In this way, naturalistic simulations generate huge amounts of empirical data for evaluating the robustness of AGI frameworks, along with many promising species that can be later instantiated in other simulated environments or even physical robots for practical applications.