Promoting reproductive isolation through diversity in on-line collective robotics

Promoting reproductive isolation through diversity in on-line collective robotics

연구 분야: Artificial Intelligence

학회: GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion

We present a behavioral diversity selection scheme that favors reproductive isolation to promote the learning of multiple task in online embodied evolutionary robotics (EER). The scheme estimates the behavior of the controllers without the need to access the agent experience, respecting thus the online, distributed properties EER. Reproductive isolation is assessed through coalescence trees and task specialization is tested on a concurrent foraging setting.