一种用于模拟人类翻译过程的活跃推理代理
1Department of Modern and Classical Language Studies, Kent State University, Kent, OH 44240, USA.
Entropy (Basel, Switzerland)
|August 29, 2024
概括
本研究概述了一个人工代理架构,使用主动推理 (AIF) 和预测处理 (PP) 建模人类翻译. 这个框架有助于模拟翻译变异和探索认知机制.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 人类翻译涉及复杂的认知过程.
- 积极推断 (AIF) 和预测处理 (PP) 为理解感知和行动提供了框架.
- 现有的模型可能无法完全捕捉人类翻译的细微差别.
研究的目的:
- 为人工翻译代理提供一种新的,层次化的嵌入式架构.
- 通过使用AIF和PP的原则来建模人类翻译过程.
- 为研究翻译背后的心理机制提供一个计算框架.
主要方法:
- 开发一个三层代理架构:感官运动,认知和现象.
- 适用于AIF原则,其中状态是依据观察和行动过渡的条件.
- 模拟不同时间尺度上运行的层之间的相互作用.
主要成果:
- 拟议的架构整合了用于翻译建模的预测处理和主动推理.
- 该模型允许模拟翻译行为的变化.
- 该框架促进了关于翻译思想的假设的生成和测试.
结论:
- 层次嵌入的AIF代理提供了一种新的计算方法来研究人类翻译.
- 这个模型为探索翻译的认知和现象方面提供了测试平台.
- 该框架提升了我们对预测,行动和翻译之间的相互作用的理解.
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