All Outputs (2)

Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture (2024)
Presentation / Conference Contribution
Le Goff, L., & Hart, E. (2024, July). Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture. Presented at GECCO 2024 Embodied and Evolved Artificial Intelligence Workshop, Melbourne, Australia

Algorithmic frameworks for the joint optimisation of a robot's design and controller often utilise a learning loop nested within an evolutionary algorithm to refine the controller associated with a newly generated robot design. Intuitively, it is rea... Read More about Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture.

Understanding fitness landscapes in morpho-evolution via local optima networks (2024)
Presentation / Conference Contribution
Thomson, S. L., Le Goff, L., Hart, E., & Buchanan, E. (2024, July). Understanding fitness landscapes in morpho-evolution via local optima networks. Presented at Genetic and Evolutionary Computation Conference (GECCO 2024), Melbourne, Australia

Morpho-Evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and control. Pre... Read More about Understanding fitness landscapes in morpho-evolution via local optima networks.