Shaping the Evolutionary Dynamics of Robot Morphology via Adaptive Control Learning
Robot co-design via bi-level optimization couples within-lifetime controller learning for fitness evaluation with cross-generational morphological evolution. Prior work has established that well-adapted morphology facilitates faster control learning, a property termed morphological intelligence. Yet how control learning reciprocally shapes morphological evolution remains unexplored. This paper examines both directions for a holistic account of brain-body interplay. We first show that morphological contributions to control learning decouple into two orthogonal dimensions. We formalize the convergence speed as morphological intelligence and identify the performance ceiling as a complementar...
| Authors | Junru Song, Yang Yang, Yaqing Xu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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