Machine Learning: Computational learning theory and applications, Knowledge discovery and acquisition, Cognitive modelling and data analysis techniques, Hybrid learning algorithms, Data and knowledge representation models, Deep learning approaches, Mutli-agent systems and learning models, Support vector machine, Intelligent information retrieval techniques, Reinforcement learning approaches, Fuzzy-based learning approaches, Machine learning for web and social network mining, Intelligent feature extraction techniques, Mobile data mining and analysis, Parallel and distributed learning algorithms, Statistical and analytical learning, Scalability and reliability of learning algorithms. Autonomous Systems: Theoretical foundations for autonomous systems, Complex and adaptive autonomous systems, Autonomous computing platforms and applications, Cognition-inspired autonomous systems, Multi-autonomous systems and applications, Autonomous algorithms and models, Adaptive and autonomous robots, Real-time autonomous systems, Smart and distributed autonomous systems, Autonomous software and operating systems, Autonomous sensors and embedded systems, Optimization and control algorithms for autonomous systems, Novel control models and structures for autonomous systems, Learning, adaptation, and estimation methods for autonomous systems, Innovative applications of autonomous systems: healthcare, agriculture, industries, military, smart cities, smart home, education, and so on.