Continual Learning in Multimodal Interactive Settings

多模式交互环境中的持续学习

• 批准号: 2427671
• 金额: --
• 依托单位: Heriot-Watt University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2427671
• 关键词: Continual; Learning; Multimodal; Interactive; Settings

In order for humans and artificial agents to communicate effectively in situated settings, agents need to be able to reason about what has been said during the dialogue and what they perceive. Despite the advances within the field of Visual Dialogue, current models based on deep neural networks are not able to continually learn new concepts and suffer from catastrophic forgetting. My research aims to bridge Continual Learning and Visual Dialogue in order to develop agents that are able to incrementally learn new concepts and skills without forgetting previous knowledge.

为了使人类和人工智能体在特定环境中有效地进行交流，智能体需要能够推理对话期间所说的内容以及他们感知到的内容。尽管视觉对话领域取得了进步，但当前基于深度神经网络的模型无法持续学习新概念并遭受灾难性遗忘。我的研究旨在弥合持续学习和视觉对话，以开发能够逐步学习新概念和技能而不忘记以前知识的智能体。