AM, an artificial intelligence approach to discovery in mathematics as heuristic search
AM, an artificial intelligence approach to discovery in mathematics as heuristic search
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AM，一种以启发式搜索方式发现数学的人工智能方法
DOI：
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发表时间：
1976
期刊：
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通讯作者：
D. Lenat
中科院分区：
文献类型：
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作者：
D. Lenat
摘要：一个名为“AM”的程序，描述模型的一个方面的小学数学研究：开发新的概念的指导下，大量的启发式规则。“数学”被认为是一种智能行为，而不是一种成品。本地专家通过议程机制进行通信，这是系统要执行的任务的全局列表，以及每个任务合理的原因。一个单一的任务可能会引导AM定义一个新的概念，或探索现有概念的某些方面，或检查一些经验数据，以进行重复，程序从议程中选择具有最佳支持理由的任务，然后执行它。最初提供了一百个非常不完整的模块，每个模块对应于一个基本的集合论概念（例如，工会）。这提供了一个明确而巨大的“空间”，AM开始探索。AM扩展了其知识库，最终重新发现了数百个常见概念（例如，数）和定理（例如，唯一因子分解）。这种似是而非的推理方法既有很大的威力，也有很大的局限性。
Abstract : A program called 'AM', is described which models one aspect of elementary mathematics research: developing new concepts under the guidance of a large body of heuristic rules. 'Mathematics' is considered as a type of intelligent behavior, not as a finished product. The local heuristics communicate via an agenda mechanism, a global list of tasks for the system to perform and reasons why each task is plausible. A single task might direct AM to define a new concept, or to explore some facet of an existing concept, or to examine some empirical data for regularities, etc. Repeatedly, the program selects from the agenda the task having the best supporting reasons, and then executes it. Each concept is an active, structured knowledge module. A hundred very incomplete modules are initially provided, each one corresponding to an elementary set-theoretic concept (e.g.,union). This provides a definite but immense 'space' which AM begins to explore. AM extends its knowledge base, ultimately rediscovering hundreds of common concepts (e.g., numbers) and theorems (e.g., unique factorization). This approach to plausible inference contains great powers and great limitations.