标题： 能否通过心理意象提升人工智能系统的思维能力？ 显示英文标题

标题： Can Mental Imagery Improve the Thinking Capabilities of AI Systems?

摘要： 尽管现有模型可以与人类交互并提供令人满意的响应，但它们缺乏自主行动或进行独立推理的能力。 此外，这些模型中的输入数据通常以明确的查询形式提供，即使某些感官数据已经获取。 另外，人工智能代理是一种计算实体，它们根据编程、数据输入和学习的知识自主执行任务和做出决策，已经取得了显著进展。 然而，它们在跨多个领域整合知识方面存在困难，而人类则不在此列。 心理意象在大脑的思维过程中起着基础性作用，这涉及基于内部多感官数据、计划的动作、需求和推理能力来执行任务。 在本文中，我们研究如何将心理意象整合到机器思维框架中，以及这如何有助于启动思维过程。 我们提出的机器思维框架集成了一个由三个辅助单元支持的认知思维单元：输入数据单元、需求单元和心理意象单元。 在此框架中，数据以自然语言句子或绘制的草图表示，既用于信息传递也用于决策目的。 我们对该框架进行了验证测试，结果已呈现并进行了讨论。 显示英文摘要

摘要： 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.