老式人工智能的概率方法

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2024-06-05 DOI:10.3103/S000510552470002X
D. V. Vinogradov, L. A. Iakimova
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引用次数: 0

摘要

摘要 本文建议使用一种概率知识提取机制来恢复老式人工智能的使用。作为一个模型任务,它建议自动生成井字游戏的规则。A. Newell 和 H. Simon 开发的著名的通用问题解决系统也使用了类似的规则。与以往科学家手动编写最优游戏策略规则不同,我们将使用概率-组合形式化方法自动生成规则。我们还将讨论所提出的方法与强化学习范式之间的关系。
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Probabilistic Approach to Good Old-Fashioned Artificial Intelligence

The paper proposes the use of a probabilistic knowledge-extraction mechanism to resume the use of good old-fashioned artificial intelligence. As a model task, it is proposed to automatically generate the rules of the Tic-Tac-Toe game. Similar rules were used in the well-known General Problem Solver system developed by A. Newell and H. Simon. Unlike the past, where scientists wrote the rules for the optimal game strategy manually, we will use a probabilistic-combinatorial formal method to generate them automatically. We will also discuss the relationship between the proposed approach and the reinforcement-learning paradigm.

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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
期刊介绍: Automatic Documentation and Mathematical Linguistics  is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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