Self-Organizing Dual-Buffer Adaptive Clustering Experience Replay (SODACER) for Safe Reinforcement Learning in Optimal Control
Researchers introduce SODACER, a reinforcement learning framework combining dual-buffer experience replay with Control Barrier Functions to enable safe optimal control of nonlinear systems. The approach demonstrates improved convergence and sample efficiency while maintaining safety constraints, with potential applications in robotics, healthcare, and large-scale optimization.