The term \u201elifelong learning agents\u201c originates primarily from the fields of artificial intelligence, automation, and robotics. It refers to computer programmes or machines that are not just trained once, but continuously learn \u2013 throughout their entire \u201elifespan\u201c. The goal: they constantly adapt to new situations, tasks, or challenges without needing to be reprogrammed each time.<\/p>\n
A vivid example is a robot in a car factory. Initially, it knows how to assemble doors. If new car models or other parts are added later, the robot can independently learn to handle them through observation, past experience, and data analysis. This allows it to develop its \u201eknowledge\u201c further and work ever more efficiently.<\/p>\n
Lifelong learning agents are therefore particularly useful when processes change frequently or a great deal of flexibility is required. In industry, they increase productivity, reduce errors, and save costs in the long run because they always stay up-to-date and can independently master complex situations. This makes them important helpers in digitalisation and the changing world of work.<\/p>","protected":false},"excerpt":{"rendered":"