Towards Real-world Continual Learning on Unrestricted Task Steams

在不受限制的任务流上实现现实世界的持续学习

• 批准号: DE230101591
• 负责人: Dr Dong Gong
• 金额: $ 29.53万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-06-01 至 2026-05-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE230101591
• 关键词: Towards; Real; world; Continual; Learning

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.

该项目旨在使机器能够持续学习而不忘记，并从包含不同任务的顺序数据流中积累知识。该项目希望将持续学习推进到不受限制的现实世界任务流中，这些任务流是长期和复杂的，并将人工智能推向人类水平的智能，可以在与世界的互动中自动进化。该项目的预期成果包括范式转换的持续学习框架和在现实场景中处理无限制任务流的技术。它们将通过增强人工智能的适用性，在国内和国际上造福社会和经济。