Towards Real-world Continual Learning on Unrestricted Task Steams

该项目旨在使机器能够不断学习而不会忘记，并从包含不同任务的连续数据流中积累知识。该项目期望将持续学习推进到不受限制的长期和复杂的现实世界任务流，并促进人工智能向人类水平的智能发展，可以在与世界的交互中自动进化。该项目的预期成果包括范式转移的持续学习框架和技术，用于处理现实世界中的不受限制的任务流。它们将通过提高人工智能的适用性，使国内和国际社会和经济受益。

This project aims to enable machines to continually learn without forgetting and accumulate knowledge from the sequential data streams containing diverse tasks. This project expects to advance the continual learning to unrestricted real-world task steams that are long-term and complex and promote artificial intelligence toward the human-level intelligence that can automatically evolve during interaction with the world. Expected outcomes of this project include the paradigm-shifting continual learning framework and techniques for handling unrestricted task steams in real-world scenarios. They will benefit society and the economy nationally and internationally by enhancing the applicability of artificial intelligence.