Parallel and distributed intelligent systems

并行分布式智能系统

• 批准号: 89-2007
• 负责人: Bhavsar, Virendrakumar
• 金额: $ 1.46万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=363834
• 关键词: Parallel; distributed; intelligent; systems

PARALLEL AND DISTRIBUTED INTELLIGENT SYSTEMSArtificial Intelligence (AI) has both engineering and scientific goals: (a) to develop systems that have some form of intelligence, and (b) to understand intelligent behavior in systems and living organisms. Since biological systems embody a marked degree of parallel and distributed functioning, we believe that the architectures of intelligent systems and/or their implementations should also embody some forms of parallel and distributed computing. The systems should also exhibit some fundamental features of evolution in nature.The long-term objective of our work has been to develop efficient models, algorithms and implementations of parallel and distributed intelligent systems. Our goal has been not only to develop and experiment with new algorithms, but to develop operational software systems that can be employed in the real world as well. Whenever opportunities arise, the outcomes of our research will be commercialized and integrated in products.We propose: (a) to devise algorithms and software systems for efficient, effective, precise, semantic matching in e-Business, e-Learning and social networking environments, (b) to utilize knowledge (e.g. gene expression data, protein-protein interaction data and regulatory elements) about existing pathways of model organism to construct partial or complete regulatory networks for non-model organisms, and (c) to develop a semantically enriched dynamic knowledge delivery system for personal learning services.

并行和并行的智能系统人工智能（AI）具有工程和科学目标：（a）开发具有某种形式智能的系统，（B）理解系统和生物体中的智能行为。由于生物系统体现了显着程度的并行和分布式功能，我们认为，智能系统的架构和/或其实现也应该体现某种形式的并行和分布式计算。系统还应该表现出一些基本的功能，在自然界中的演变。我们的工作的长期目标是开发有效的模型，算法和实现的并行和分布式智能系统。我们的目标不仅是开发和试验新的算法，而且是开发可用于真实的世界的操作软件系统。只要有机会，我们的研究成果将被商业化并整合到产品中。我们建议：（a）设计算法和软件系统，以便在电子商务、电子学习和社交网络环境中进行高效、有效、精确的语义匹配，（B）利用知识（例如基因表达数据，蛋白质-蛋白质相互作用数据和调节元件）关于模式生物的现有途径，以构建非模式生物的部分或完整的调节网络，以及（c）开发一个语义丰富的动态知识传递系统，为个人学习服务。