Decentralized Fused-Learner Architectures for Bayesian Reinforcement Learning

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Intelligence Pub Date : 2024-02-01 DOI:10.1016/j.artint.2024.104094

Augustin A. Saucan, Subhro Das, M. Win

引用次数: 0

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贝叶斯强化学习的分散融合学习器架构

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来源期刊

Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

11.20

自引率

1.40%

发文量

118

审稿时长

8 months

期刊介绍： The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.

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