Task Transition

Task transition research focuses on how systems, both biological and artificial, adapt and perform efficiently when switching between different tasks or subtasks. Current research explores this through various lenses, including developing algorithms for detecting task boundaries and managing task interference in large language models, designing robotic control systems that smoothly transition between actions, and building computational models of the brain's task-switching mechanisms using spiking neural networks and other architectures. These advancements have implications for improving human-robot collaboration, optimizing autonomous systems, and furthering our understanding of cognitive processes in the brain.