Programs as Causal Models: Speculations on Mental Programs and Mental Representation
Programs as Causal Models: Speculations on Mental Programs and Mental Representation
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DOI：
10.1111/cogs.12062
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发表时间：
2013-08-01
影响因子：
2.5
通讯作者：
Oaksford, Mike
中科院分区：
文献类型：
--
作者：
Chater, Nick;Oaksford, Mike
朱迪亚·珀尔认为，反事实和因果关系是智能的核心，无论是自然的还是人工的，并帮助创建了一个丰富的数学和计算框架，用于正式分析因果关系。在这里，我们画出这些概念和认知科学中的各种当前问题之间的联系，包括心理程序和心理表征的性质。我们认为，程序（包括算法和数据结构）有一个因果（反事实支持）结构，这些反事实可以揭示心理表征的性质。程序还可以提供外部世界的因果模型。我们认为，这样的模型在感知、认知和语言处理中无处不在。
Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of mental programs and mental representation. We argue that programs (consisting of algorithms and data structures) have a causal (counterfactual-supporting) structure; these counterfactuals can reveal the nature of mental representations. Programs can also provide a causal model of the external world. Such models are, we suggest, ubiquitous in perception, cognition, and language processing.