A Reinforcement Learning Intelligent Deductive Model with Pretrained Sequence Information

IF 1.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Bio-Inspired Computation Pub Date : 2023-01-01 DOI:10.1504/ijbic.2023.10059183

Hao Yu, Sizhao Li, Huosheng Xu, Xinyu Han

引用次数: 0

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基于预训练序列信息的强化学习智能演绎模型

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Bio-Inspired Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

5.10

自引率

5.70%

发文量

审稿时长

>12 weeks

期刊介绍： IJBIC discusses the new bio-inspired computation methodologies derived from the animal and plant world, such as new algorithms mimicking the wolf schooling, the plant survival process, etc. Topics covered include: -New bio-inspired methodologies coming from creatures living in nature artificial society- physical/chemical phenomena- New bio-inspired methodology analysis tools, e.g. rough sets, stochastic processes- Brain-inspired methods: models and algorithms- Bio-inspired computation with big data: algorithms and structures- Applications associated with bio-inspired methodologies, e.g. bioinformatics.