Aims:

1. To serve as a leading platform for disseminating cutting-edge research in the fields of artificial intelligence (AI) and autonomous systems.
2. To foster interdisciplinary collaboration and dialogue among researchers, practitioners, and policymakers working in AI and autonomous systems.
3. To address fundamental theoretical issues, practical challenges, and ethical considerations related to the development and deployment of AI and autonomous systems.
4. To promote innovation and advancements in AI algorithms, methodologies, and technologies, including machine learning, deep learning, natural language processing, computer vision, robotics, and intelligent agents.
5. To explore the societal impacts and implications of AI and autonomous systems across various domains, including healthcare, transportation, manufacturing, finance, education, and entertainment.

Scope: The Journal Covers broad range of topics but is not limited to:

1. Artificial Intelligence (AI):
• AI algorithms, methodologies, and technologies,
• Machine learning
• Deep learning
• Natural language processing
• Knowledge representation and reasoning
• Planning and decision-making systems
• Cognitive models and computational intelligence
• Computer vision
• Robotics 
• Intelligent agents
• Artificial Intelligence – Theory and Practice 
• Approximate and Probabilistic Reasoning 
• Artificial Intelligence in Medicine and Healthcare 
• Autonomous Vehicles 
• Big Data  
• Bioinformatics 
• Biometric Systems 
• Brain-Computer Interface 
• Computational Intelligence 
• Computer Visions 
• Distributed Artificial Intelligence 
• Deep Learning 
• Evolutionary Systems 
• Fuzzy Systems 
• Genetic Algorithms 
• Graphical Models in Machine Learning 
• Human-computer Interface including Assistive Systems 
• Image Processing and Understanding 
• Knowledge-based and agent-based systems  
• Kernel Methods in Machine Learning 
• Natural Language Processing and Understanding 
• Neural Networks 
• Optimization 
• Planning and Scheduling 
• Pattern Recognition 
• Quantum Methods in Machine Learning 
• Robotics 
• Statistical Learning Theory 
2. Autonomous Systems:
• Robotics and autonomous agents
• Autonomous vehicles and drones
• Intelligent control systems
• Swarm robotics and multi-agent systems
• Human-robot interaction and collaboration
• Perception, navigation, and localization
3. Applications and Domains:
• Healthcare: AI-driven diagnostics, personalized medicine, medical imaging analysis
• Transportation: Autonomous vehicles, traffic management, smart transportation systems
• Manufacturing: Robotics automation, smart factories, predictive maintenance
• Finance: Algorithmic trading, fraud detection, risk assessment
• Education: Intelligent tutoring systems, adaptive learning platforms
• Entertainment: Virtual assistants, recommendation systems, game AI
4. Ethical, Legal, and Societal Implications:
• Ethical considerations in AI and autonomous systems design and deployment
• Bias and fairness in AI algorithms
• Privacy and security concerns
• Regulation and policy implications
• Socio-economic impacts and ethical governance frameworks
5. Methodologies and Tools:
• Development frameworks and platforms for AI and autonomous systems
• Simulation and modeling techniques
• Evaluation metrics and benchmark datasets
• Human-centered design principles
6. Emerging Trends and Future Directions:
• Quantum computing and AI
• Edge computing and IoT integration
• Explainable AI and transparent AI systems
• Bio-inspired and neuromorphic computing
• Interdisciplinary research at the intersection of AI, robotics, and other fields.

By encompassing these aims and scope, the "Journal of Artificial Intelligence and Autonomous Systems" aims to contribute significantly to the advancement of knowledge and innovation in AI and autonomous systems, addressing both theoretical advancements and practical applications while considering the broader societal impacts and ethical considerations.

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