International Journal of Machine Learning and Cybernetics

期刊简介：Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.Key research areas to be covered by the journal include:Machine Learning for modeling interactions between systemsPattern Recognition technology to support discovery of system-environment interactionControl of system-environment interactionsBiochemical interaction in biological and biologically-inspired systemsLearning for improvement of communication schemes between systems

【译文】控制论关注描述日常生活中的系统之间无处不在的复杂相互作用和相互关系。机器学习发现系统变量及其变量集之间的基本功能关系。机器学习与控制论的融合旨在通过从数据中学习的不同机制来发现系统之间各种形式的相互作用。《国际机器学习与控制论杂志》（IJMLC）专注于机器学习与控制论交汇处出现的关键研究问题，并作为该领域最新进展快速传播的广泛论坛。IJMLC强调受工程、数学、认知科学和应用等不同贡献学科启发的机器学习与控制论方案的混合发展。IJMLC的范围包括与机器学习与控制论所有方面相关的新思想、设计选择、实现和案例研究。该期刊将涵盖的关键研究领域包括：用于建模系统之间相互作用的机器学习、支持发现系统-环境交互的识别技术、系统-环境交互的控制、生物和生物启发的系统中的生化相互作用、系统之间通信方案改进的学习