Risk management for self-adapting self-organizing emergent multi-agent systems performing dynamic task fulfillment
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10458-014-9274-0.pdf
Reference60 articles.
1. Akour, M., Jaidev, A., & King, T.M. (2011). Towards Change Propagating Test Models in Autonomic and Adaptive Systems. In Proceedings of the International Conference on Engineering of Computer-Based Systems, ECBS ’11 (pp. 89–96). IEEE Computer Society.
2. Barbucha, D., & Jedrzejowicz, P. (2009). Agent-based approach to the dynamic vehicle routing problem. In Proceedings of the International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS’ 09 (pp. 169–178). Berlin: Springer.
3. Berbeglia, G., Cordeau, J. F., Gribkovskaia, I., & Laporte, G. (2007). Static pickup and delivery problems: A classiffication scheme and survey. TOP, 15(1), 1–31.
4. Coelho, D. K., Roisenberg, M., de Freitas Filho, P. J., & Jacinto, C. M. C. (2005). Risk assessment of drilling and completion operations in petroleum wells using a monte carlo and a neural network approach. In Proceedings of the Winter Simulation Conference, WSC ’05 (pp. 1892–1897). Winter Simulation Conference.
5. Davidsson, P., Persson, J. A., & Holmgren, J. (2007). On the integration of agent-based and mathematical optimization techniques. In Proceedings of the International Symposium on Agent and Multi-Agent Systems, KES-AMSTA ’07 (pp. 1–10). Berlin: Springer.
Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Self-adaptive systems: A systematic literature review across categories and domains;Information and Software Technology;2022-08
2. Introduction to the Metrics Theme;Accelerating Digital Transformation;2022
3. Introduction to the Continuous Architecture Theme;Accelerating Digital Transformation;2022
4. Introduction to the AI Engineering Theme;Accelerating Digital Transformation;2022
5. Introduction to the Customer Data and Ecosystem-Driven Development Theme;Accelerating Digital Transformation;2022
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3