Student opportunities

Evolutionary Robotics

  • Voxel-based soft robots (VSRs)

    • Cooperative co-evolution of body and brain of VSRs

    • Learning techniques for the controllers of VSRs: reinforcement learning

    • Auto-assembly of VSRs

    • Grammar-based generative encoding for developing (phenotypically plastic) modular robots

    • Resolution-agnostic representation for evolution of closed-loop controllers of VSRs

    • Social/cultural/imitation learning in VSRs

    • Distributed world models for reconfigurable soft robots

    • Impact on evolvability of the controller of the replacement of rigid parts with soft ones in modular robots

  • Real robots

    • PushGP on mobile robots (Thymio-II): a machine-friendly representation for robotic agents controllers

Artificial Life

  • Optimization of the policies of a few ruling agents in a multi-agent systems

  • Modeling and simulation of the academic publishing system for characterizing how incentives of different actors impact on the overall effectiveness

Algorithmical improvements

  • Two- or multi-stage quality-diversity evolution with a representation based on anchor solutions

  • Co-evolutionary map-elites

See also the student opportunities at the Machine Learning Lab.