基于情境信号的连续多任务学习 | |
曾冠雄 | |
2019-05-31 | |
页数 | 82 |
学位类型 | 硕士 |
中文摘要 | 人工神经网络(Artificial Neural Networks, ANN)是处理识别和分类任务的强大工具,因为它们可以学习输入和输出之间复杂的映射关系。但是,目前的神经网络所能学习的映射规则通常是单一且固定的。这限制了网络在复杂和动态变化的环境下工作的能力。当神经网络的输出需要根据情境不断变化时,这就对现有的神经网络提出了很大的挑战。在灵长类大脑中,前额叶皮层(Prefrontal Cortex, PFC)会依据情境信号灵活处理当前的输入,执行不同的任务,另外,与当前大多数人工神经网络不同,灵长类能够连续地逐项学习这些情境依赖的处理规则,从而使得其灵活性能够不断地增加。受大脑这些特性的启发,本文提出了一种新的方法,包括正交权重修改(Orthogonal Weights Modification, OWM)算法和情境依赖处理(Context-dependent Processing, CDP)模块。该方法使神经网络能够基于情境连续地学习不同的映射规则。 |
英文摘要 | Artificial neural networks (ANN) are powerful tools for recognition and classification as they learn sophisticated mapping rules between the inputs and the outputs. However, the rules that learned by the majority of current ANN used for pattern recognition are largely fixed and do not vary with different conditions. This limits the network's ability to work in more complex and dynamical situations in which the mapping rules themselves are not fixed but constantly change according to contexts, such as different environments and goals. In addition, unlike most artificial neural networks in use, primates are able to continuously learn these context-dependent processing rules one by one, so that their flexibility can be continuously increased.Inspired by the role of the prefrontal cortex (PFC) in mediating context-dependent processing in the primate brain, here we propose a novel approach, involving a learning algorithm named Orthogonal Weights Modification (OWM) with the addition of a Context-dependent Processing (CDP) module, that enables networks to continually learn different mapping rules in a context-dependent way. Inspired by these characteristics of the brain, we propose a new method, including OWM learning algorithm and CDP module. This method enables the neural network to continuously learn different mapping rules based on context. |
关键词 | 前额叶皮层 正交权重修改 情境依赖处理 灾难性遗忘 连续学习 多任务学习 |
语种 | 中文 |
七大方向——子方向分类 | 类脑模型与计算 |
文献类型 | 学位论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23772 |
专题 | 脑网络组研究 |
推荐引用方式 GB/T 7714 | 曾冠雄. 基于情境信号的连续多任务学习[D]. 北京. 中国科学院大学,2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
基于情境信号的连续多任务学习.pdf(4369KB) | 学位论文 | 开放获取 | CC BY-NC-SA |
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