CAREER: Biologically Inspired Learning Algorithms for Artificial Sensorimotor Systems

职业：人工感觉运动系统的生物启发学习算法

• 批准号: 0347132
• 负责人: Daniel Lee
• 金额: --
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347132&HistoricalAwards=false
• 关键词: CAREER; Biologically; Inspired; Learning; Algorithms

This project will investigate biologically-inspired methodologies and algorithms for several important problems in machine learning and AI: unsupervised feature learning, multi-modal integration of sensory data, and learning for real-time robotic systems with embedded sensors and actuators. The project will pursue both theoretical investigations of nonlinear properties of neurons and synapses and their role in processing of perceptual (visual, auditory, olfactory) stimuli, as well as the applications of such properties to the design of novel algorithms and architectures for processing of multi-modal perceptual stimuli. This research will integrate advances in the understanding of biological systems by building more advanced artificial sensorimotor systems. This project integrates research and an educational agenda that includes teaching and participation of students from the broader community in activities related to the overall goals of this research.

该项目将针对机器学习和人工智能中的几个重要问题研究受生物学启发的方法和算法：无监督特征学习、传感数据的多模态集成以及具有嵌入式传感器和执行器的实时机器人系统的学习。该项目将追求神经元和突触的非线性特性及其在感知（视觉、听觉、嗅觉）刺激处理中的作用的理论研究，以及这些特性在设计用于处理多个神经元和突触的新颖算法和架构中的应用。 -模态知觉刺激。这项研究将通过构建更先进的人工感觉运动系统来整合对生物系统理解的进步。 该项目整合了研究和教育议程，其中包括来自更广泛社区的学生的教学和参与与本研究总体目标相关的活动。