arXiv:2507.12555cs.LGcs.AI2025-07

让AI像人一样用内心图像思考,提升自主决策能力。

Can Mental Imagery Improve the Thinking Capabilities of AI Systems?

  • 构建包含内在图像、需求与输入数据的思维框架
  • 通过自然语言和草图实现多模态信息交互
  • 适合研究通用AI与自主智能体的学者参考

现有模型虽能与人类交互并给出满意回答,但缺乏自主行动或独立推理能力。输入数据通常为显式查询,即使已有感知数据。尽管人工智能代理在任务执行和决策方面取得进展,但在跨领域知识整合上仍远不如人类。心智意象在大脑思维过程中起基础作用,涉及基于内部多感官数据、计划行为、需求和推理能力的任务执行。本文探究如何将心智意象融入机器思维框架,并分析其对启动思维过程的潜在益处。提出的机器思维框架包含一个认知思维单元,以及三个辅助单元:输入数据单元、需求单元和心智意象单元。在此框架中,数据以自然语言句子或手绘草图表示,兼具信息传递与决策支持功能。我们对框架进行了验证测试,结果予以呈现与讨论。

原文摘要 · Abstract (English)

Although existing models can interact with humans and provide satisfactory responses, they lack the ability to act autonomously or engage in independent reasoning. Furthermore, input data in these models is typically provided as explicit queries, even when some sensory data is already acquired. In addition, AI agents, which are computational entities designed to perform tasks and make decisions autonomously based on their programming, data inputs, and learned knowledge, have shown significant progress. However, they struggle with integrating knowledge across multiple domains, unlike humans. Mental imagery plays a fundamental role in the brain's thinking process, which involves performing tasks based on internal multisensory data, planned actions, needs, and reasoning capabilities. In this paper, we investigate how to integrate mental imagery into a machine thinking framework and how this could be beneficial in initiating the thinking process. Our proposed machine thinking framework integrates a Cognitive thinking unit supported by three auxiliary units: the Input Data Unit, the Needs Unit, and the Mental Imagery Unit. Within this framework, data is represented as natural language sentences or drawn sketches, serving both informative and decision-making purposes. We conducted validation tests for this framework, and the results are presented and discussed.

AI思维心智意象自主决策

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