Artificial Intelligence has an important place in the scientific community as a result of its successful outputs in terms of different fields. In time, the field of Artificial Intelligence has been divided into many sub-fields because of increasing number of different solution approaches, methods, and techniques. Machine Learning has the most remarkable role with its functions to learn from samples from the environment. On the other hand, intelligent optimization done by inspiring from nature and swarms had its own unique scientific literature, with effective solutions provided for optimization problems from different fields. Because intelligent optimization can be applied in different fields effectively, this study aims to provide a general discussion on multidisciplinary effects of Artificial Intelligence by considering its optimization oriented solutions. The study briefly focuses on background of the intelligent optimization briefly and then gives application examples of intelligent optimization from a multidisciplinary perspective.
Multi-Agent Intelligence for Multidisciplinary Decision-Making in Gastrointestinal Oncology
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine（上海第九人民医院，上海交通大学医学院）；Renji Hospital, Shanghai Jiao Tong University School of Medicine（仁济医院，上海交通大学医学院）；Shanghai Institute of Infectious Disease and Biosecurity, Fudan University（上海市传染病防治研究所暨生物安全研究所，复旦大学）；Shanghai Health Development Research Center (Shanghai Medical Information Center)（上海市卫生健康发展研究中心（上海市医疗信息中心））；Shanghai Kupas Technology Co., Ltd.（上海库帕斯科技有限公司）
Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds
Catholic University of Sacred Heart（圣心天主教大学）；Istituto Auxologico Italiano IRCCS（意大利奥索洛吉科研究所）；University of Milano - Bicocca（米兰比可卡大学）；Virtual Reality Medical Center（虚拟现实医疗中心）；Interactive Media Institute（交互媒体研究所）
A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work
Joint Research Centre, European Commission（欧盟委员会联合研究中心）；Universitat Pompeu Fabra（庞培法布拉大学）；Universitat Politècnica de València（瓦伦西亚理工大学）；University of Cambridge（剑桥大学）
Artificial Intelligence : from Research to Application ; the Upper-Rhine Artificial Intelligence Symposium (UR-AI 2019)
TriRhenaTech联盟大学及其合作伙伴在2019年3月13日在奥芬堡举行的三国会议“人工智能：从研究到应用”上展示了他们在人工智能领域的能力以及与行业的跨境合作。TriRhenaTech联盟是上莱茵河三国大都市区的大学网络，包括位于富特旺根、凯泽斯滕、卡尔斯鲁厄和奥芬堡的德国应用科学大学，巴登-符腾堡州合作州立大学Loerrach，法国大学网络阿尔萨斯理工大学，瑞士国立大学（由14所工程、建筑和管理领域的“高等院校”组成）和瑞士西北应用科学与艺术大学（University of Applied Sciences and Arts Northwestern Switzerland）。该联盟的共同目标是加强知识、研究和技术的转移，以及学生的跨境流动。
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence
University of Brasilia（巴西利亚大学）；University of Sao Paulo（圣保罗大学）
本文回顾了23年前提出的“一次学习”机制，以及随后在图像分类中的“一次性学习”和在客观检测中的“You Only Look Once - YOLO”的成功。分析了人工智能（AI）的发展现状，提出AI应明确划分为人工人类智能（AHI）、人工机器智能（AMI）和人工生物智能（ABI），这也将是AI理论和应用发展的主要方向。作为人工智能分支的分水岭，讨论了一些分类标准和方法：1）面向人类、面向机器和面向生物的人工智能研发; 2）通过模糊度上升或模糊度下降处理的信息输入; 3）使用一个/几个或大样本进行知识学习。
