Advancing Neuromorphic Computing

This chapter examines the development of spiking neural networks through hardware-in-the-loop evolution, focusing on the role of FPGA technology and the trade-offs between custom and flexible architectures. It emphasizes the significance of software development within the neuromorphic community, advocating for open-source frameworks to enhance accessibility. The conversation also explores the integration of evolutionary algorithms into various applications, particularly in robotic systems, while addressing the challenges of dynamic environments and lifelong learning.