对注意的再思考:一个注意的强化学习模型

发布时间：2018-04-12 09:40

  本文选题：注意 + 强化学习　； 参考：《应用心理学》2017年01期

【摘要】：本文在分析总结现有注意理论的基础上,假设注意是一种信息选择现象,而非心理结构或资源。通过借鉴人工智能领域强化学习算法的思想,笔者提出了一种可以表现出注意现象的人类强化学习模型。该模型描述了人与环境交互的过程:人接受环境的反馈,根据自身心理状态调整行为策略,以最大化所获收益。该过程中,注意体现为高价值信息逐渐获得优先加工的现象。因此,本文对注意的本质进行了重新思考,为未来注意研究提供了新思路。
[Abstract]:On the basis of analyzing and summarizing the existing attention theory, this paper assumes that attention is a phenomenon of information selection, not a psychological structure or resource.By learning from the idea of reinforcement learning algorithm in artificial intelligence field, the author proposes a human reinforcement learning model which can show attention phenomenon.The model describes the process of interaction between human and environment: people receive feedback from the environment and adjust their behavior strategies according to their psychological state to maximize the benefits.In this process, attention is reflected in the phenomenon that high-value information gradually obtains priority processing.Therefore, this paper reconsiders the essence of attention and provides new ideas for future attention research.
【作者单位】： 浙江大学心理与行为科学系;
【基金】：国家自然科学基金项目(31571119,31600881,61431015) 中央高校基本科研业务费专项资金资助
【分类号】：B842.3
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本文编号：1739198