Peter Fine

Papers

Total Citations

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About

Dr. Peter Fine is a researcher whose work lies at the intersection of evolutionary robotics, artificial neural networks, and embodied cognition. His most significant contribution is the pioneering investigation of GasNets—a unique class of artificial neural networks that incorporate an analogue of biological volume signalling, inspired by the diffusion of nitric oxide. In his highly cited 2010 study, "Spatial, temporal, and modulatory factors affecting GasNet evolvability in a visually guided robotics task," Fine systematically dissected how spatial and temporal dynamics influence the evolvability of these networks, demonstrating their capacity for complex, visually guided behavior. This work, with 24 citations, remains a foundational reference for researchers exploring non-traditional neural architectures. Additionally, his 2007 paper, "Adapting to Your Body," reflects a deep interest in how artificial systems can adapt to morphological changes, a key theme in developmental robotics. Though his citation counts are modest, Fine’s contributions are notable for their conceptual depth and influence on the design of adaptive, biologically-plausible control systems. His research offers valuable insights for students and scholars seeking to understand how neural dynamics and embodiment shape intelligent behavior in artificial agents.