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 (ongoing)
Auto-assembly of VSRs (ongoing, but expandable)
Grammar-based generative encoding for developing (phenotypically plastic) modular robots (ongoing)
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
Hierarchical (module role-based or environmental context-based) policies for modular robots
Real robots
PushGP on mobile robots (Thymio-II): a machine-friendly representation for robotic agents controllers
Hybrid (soft & rigid) robot simulation and optimization
Design and development of an interactive software tool for definining robot morphologies
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 (ongoing)
Evolutionary optimization of synapsis-wise and reward-driven autoadaptation rules
Reconfigurable Neural Cellular Automata
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.