About the Journal

Artificial Intelligence, Machine Learning, and Autonomous Systems (AMLAS) is a peer-reviewed, open-access scholarly journal committed to advancing frontier research in intelligent computation, self-learning models, and autonomous technologies. AMLAS serves as an interdisciplinary platform uniting academics, industry experts, and policymakers to share original research and practical breakthroughs in AI-driven systems. The journal publishes cutting-edge work on machine learning algorithms, robotics, autonomous agents, adaptive control systems, and ethical AI deployment. It further emphasizes innovations in computer vision, reinforcement learning, human-machine collaboration, and context-aware automation. AMLAS values academic rigor, reproducibility, and societal relevance—delivering impactful content that catalyzes responsible tech adoption. With a global perspective and quarterly frequency, AMLAS maintains strict double-blind peer review standards and aims to cultivate a diverse body of knowledge shaping the future of autonomy. The journal stands at the convergence of intelligence, automation, and accountability in the age of transformative digital systems.

Journal Name: Artificial Intelligence, Machine Learning, and Autonomous Systems (AMLAS)
ISSN: 2991-0045
Impact Factor: 6.6 (By ResearchBib)
Journal Initials: AMLAS
Research Scope: Artificial Intelligence, Machine Learning, Robotics, Reinforcement Learning, Autonomous Vehicles, Human-Machine Interaction, AI Ethics, Intelligent Control Systems, Computer Vision
Publication Mode: Digital (On this Website)
Frequency: Annual (1 Volume per Year)
Launch Year: 2017
Review Mode: Double Blind Peer Review
Plagiarism Allowed: 10% (as per Turnitin)
Coverage: Worldwide
Language: English