通过 AND/OR 树向后推理来解决问题
Jeroen Olieslagers1, Zahy Bnaya2, Yichen Li3
1Center for Neural Science, New York University, New York, NY, United States.
概括
我们引入了 AND/OR 树,这是解决问题时向后推理的新框架. 这个模型有效地解释了人类在复杂的题中的行为,为认知过程提供了洞察力.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 心理学 心理学 心理学
背景情况:
- 解决问题无处不在,但缺乏一个统一的框架,以向后推理.
- 现有的模型没有完全捕捉到人类如何将问题分解为子目标和行动.
研究的目的:
- 引入 AND/OR 树作为一个新的向后推理表征.
- 调查 AND/OR 树对人类解决问题行为的预测能力.
- 在 AND/OR 树中建模人类搜索策略.
主要方法:
- 开发 AND/OR 树框架来表示解决问题的过程.
- 进行一项研究,参与者解决了决定性,长时间的题.
- 模拟参与者的搜索行为,使用一个单参数算法,适合单个数据.
主要成果:
- AND/OR树成功地解释了大多数参与者在解过程中的行为.
- 开发的搜索算法捕获了人类游戏总结统计数据中的关键趋势.
- 该模型在代表向后推理方面展示了心理上的可信性.
结论:
- AND/OR树为向后推理提供了一个有前途的代表性框架.
- 这种方法为解决问题的人类认知策略提供了宝贵的见解.
- 进一步的研究可以将这个框架扩展到更复杂的问题领域.
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