Title : A boxology of neuro-symbolic systems

Presenter Frank van Harmelen & Annette ten Teije
Abstract We try to describe a large variety of systems that combine machine learning and knowledge representation with a small set of compositional architectural patterns. The hope is that this will help to systematise the literature, and that it will help to understand which combinations of machine learning and knowledge representations serve which purposes.

Title : Analysing the Relative Importance of Robot Brains and Bodies

Presenter Milan Jelisavcic
Abstract The evolution of robots, when applied to both the morphologies and the controllers, is not only a means to obtain high-quality robot designs, but also a process that results in many body-brain-fitness data points. Inspired by this perspective, in this paper we investigate the relative importance of robot bodies and brains for a good fitness. We introduce a method to isolate and quantify the effect of the bodies and brains on the quality of the robots and perform a case study. The method is general in that it is not restricted to evolutionary systems. For the case study, we use a system of modular robots, where the bodies are evolvable and the brains are evolvable and learnable. These case studies validate the usefulness of our method and deliver interesting insights into the interplay between bodies and brains in evolutionary robotics.