构建振荡神经网络和量子类似认知以及量子启发的计算和人工智能之间的桥梁
Andrei Khrennikov1, Atsushi Iriki2, Irina Basieva1
1Center for Mathematical Modeling in Physics and Cognitive Sciences Linnaeus University, Växjö, SE 351 95, Sweden.
Bio Systems
|September 1, 2025
概括
量子模型将大脑振荡与认知过程联系起来, 这种框架可以在振荡网络中使用量子启发计算 (QIC) 实现量子样人工智能 (QLAI).
科学领域:
- 认知神经科学
- 量子信息理论
- 计算心理学
背景情况:
- 量子类型 (QL) 建模将量子理论应用于决策和认知心理学,解释悖论,但缺乏神经链接.
- 现有的QL模型没有直接连接到大脑的神经生理学和信息处理机制.
研究的目的:
- 通过探索神经振荡如何产生QL行为来弥合神经生理学,神经心理学和认知心理学.
- 提出一个量子理论框架,QL振荡性认知,连接认知,决策和神经元振荡.
- 为理解心灵与物质的关系和感知的性质奠定基础.
主要方法:
- 通过神经元振荡和量子计算 (QIC) 来启发.
- 开发了"QL振荡认知"的量子理论框架.
- 在这个框架内提出了四个可测试的猜测,其中一个是使用QL状态纠的绑定问题.
主要成果:
- 提出了一个新的框架 (QL振荡认知),将神经振荡与QL行为整合起来.
- 建议基本的认知过程与量子原理保持一致.
- 假设QL状态在神经网络中的纠可以解决结合问题.
结论:
- 基本的认知过程可以根据量子原理运行.
- 人类人工智能可以通过量子理论法则来处理信息,从而获得量子类人工智能 (QLAI).
- 使用执行QIC的振荡网络可以有效地实现QLAI.
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