Abstract: Optimization problems in real-world applications often involve dynamic environmental changes, requiring algorithms to adapt quickly, track optimal solutions, and maintain efficiency.

Abstract: Evolutionary reinforcement learning (ERL), which integrates the evolutionary algorithms (EAs) and reinforcement learning (RL) for optimization, has demonstrated remarkable performance ...

New research is significantly revising a widely cited evolutionary model, the Inhibitory Cascade Mode (ICM). Benjamin Auerbach, professor in the Department of Ecology and Evolutionary Biology at the ...

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...