CAREER: Biologically Inspired Learning Algorithms for Artificial Sensorimotor Systems

这个项目将研究机器学习和人工智能中几个重要问题的生物启发的方法和算法：无监督特征学习，传感器数据的多模式集成，以及带有嵌入式传感器和执行器的实时机器人系统的学习。该项目将对神经元和突触的非线性特性及其在知觉(视觉、听觉、嗅觉)刺激处理中的作用进行理论研究，并将这些特性应用于设计处理多模式知觉刺激的新算法和体系结构。这项研究将通过建立更先进的人工感觉运动系统来整合生物系统理解方面的进展。该项目结合了研究和教育议程，其中包括教学和更广泛社区的学生参与与本研究总体目标有关的活动。

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.