US-United Kingdom Cooperative Science: A Theoretical Study of the Perceptual Prerequisites of Learning

该奖项将支持马萨诸塞大学的安德鲁·巴托博士和英国剑桥大学生理实验室的霍勒斯·巴洛教授之间的合作研究。巴托博士将在剑桥国王学院研究中心休六个月的假。他将参与研究中心的生物信息处理计划，并将与巴洛博士合作，制定和评估与促进目标导向学习有关的感知原则。研究人员建议调查感官输入的编码方案如何最大限度地依赖于要学习的特定行为来促进学习。他们将研究各种现有的和新的编码原则，关于它们对目标导向学习的影响。他们将特别关注巴洛提出的关于最小熵编码原理的想法。研究人员计划从理论上比较和对比这些原则，并在需要的情况下，通过计算实验进行比较。他们还将把他们的理论发现与神经元群体表现出的编码原理相关的数据联系起来。巴托博士是实时计算学习问题领域公认的领导者，而巴洛博士多年来一直是大脑感知领域的杰出研究人员。这项研究的结果将对理解生物神经网络和人工神经网络之间的理论联系做出重要贡献。

This award will support collaborative research between Dr. Andrew Barto, University of Massachusetts, and Professor Horace Barlow, Physiological Laboratory, Cambridge University, England. Dr. Barto will spend a six month sabbatical at the King's College Research Center at Cambridge. He will participate in the Research Center's Program on Biological Information Processing and will collaborate with Dr. Barlow on formulating and evaluating perceptual principles that are linked to the facilitation of goal-directed learning. The investigators propose to investigate how encoding schemes for sensory input, depending minimally on the specific behavior to be learned, can facilitate that learning. They will examine a variety of existing and novel coding principles with respect to their implications for goal-directed learning. They will focus particularly on the ideas being developed by Barlow on minimum entropy encoding principles. The investigators plan to compare and contrast these principles theoretically and, where need arises, via computational experiments. They will also relate their theoretical findings to data relevant to the coding principles exhibited by populations of neurons. Dr. Barto is a recognized leader in the field of real-time computational learning problems and Dr. Barlow has been for many years a preeminent researcher in brain perception. The results of this research should make an important contribution to understanding the theoretical link between biological and artificial neural networks.