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Parallel reasoning: a virtual-real interactive knowledge collaboration framework based on ACP approach
- Chinese Journal of Intelligent Science and Technology Vol. 5, Issue 1, Pages: 69-82(2023)
- 作者机构：
1. 安徽大学人工智能学院，安徽 合肥 230601
2. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
3. 青岛智能产业技术研究院，山东 青岛 256200
4. 之江实验室图计算研究中心，浙江 杭州 311100
5. 澳门科技大学创新工程学院，澳门 999078
- 作者简介：
- 基金信息：The National Key Research and Development Program of China(2018AAA0101502)
DOI：10.11959/j.issn.2096-6652.202254
CLC： TP301-
Published Online：2023-03，
Published：15 March 2023
- 稿件说明：
移动端阅览
Xiao WANG, Linyao YANG, Bin HU, et al. Parallel reasoning: a virtual-real interactive knowledge collaboration framework based on ACP approach[J]. Chinese journal of intelligent science and technology, 2023, 5(1): 69-82.
Xiao WANG, Linyao YANG, Bin HU, et al. Parallel reasoning: a virtual-real interactive knowledge collaboration framework based on ACP approach[J]. Chinese journal of intelligent science and technology, 2023, 5(1): 69-82. DOI： 10.11959/j.issn.2096-6652.202254.
摘要
知识图谱基于结构化三元组描述事实知识，能够有效刻画现实世界实体间的语义关系，已成为新一代人工智能的关键共性技术。总结了多源知识图谱的发展概况、典型应用以及知识协同存在的问题，提出了一种基于ACP方法的多源知识图谱知识协同框架——平行推理，该框架基于人工系统、计算实验和平行执行实现了多源知识的抽取、融合补全及无偏化应用。以电网低压减载场景为例，基于仿真试验验证了平行推理对解决复杂系统管控问题的有效性。
Abstract
Knowledge graph represents empirical knowledge based on structured triples
which can effectively describe the semantic relationships between real-world entities.Knowledge graph has become a critical standard technology of the new generation of artificial intelligence.The development
typical applications of multi-source knowledge graphs
and problems of knowledge collaboration were summarized.A multi-source knowledge graph collaboration framework based on ACP approach
i.e.
parallel reasoning
was proposed
which realized the extraction
fusion
completion
and unbiased application of multi-source heterogeneous knowledge based on artificial systems
computational experiments
and parallel execution.In the end
simulation experiments were conducted on power grid dispatching to evaluate the effectiveness of parallel learning for solving the management and control problems of complex systems.
关键词
Keywords
references
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