Incremental reinforcement learning for multi-objective analog circuit design acceleration
Incremental reinforcement learning for multi-objective analog circuit design acceleration is a scholarly work, published in 2024 in ''Engineering Applications of Artificial Intelligence''. The main subjects of the publication include electronic circuit, genetic programming, computer science, reinforcement learning, nanoelectronics, process, circuit design, field-programmable gate array, analog electronics, and computer engineering. The paper proposes a simulation-based optimization method based on a deep reinforcement learning (DRL) agent to optimize analog circuits and accelerate the design process.