Journal of Experimental & Theoretical AI - Impact Factor

About: The Journal of Experimental & Theoretical Artificial Intelligence (JETAI) focuses on advancements in artificial intelligence (AI) through both experimental and theoretical approaches. It provides a platform for researchers, practitioners, and professionals to publish original research articles, reviews, and theoretical papers that contribute to the understanding and development of AI methodologies.
Publication Frequency: JETAI publishes regularly to ensure timely dissemination of research findings and advancements in artificial intelligence.
Peer Review: All submissions undergo rigorous peer review by experts in the field to maintain high academic standards and ensure the validity and significance of published research.
Impact: The Journal of Experimental & Theoretical Artificial Intelligence aims to advance the field by promoting innovative research that enhances the understanding and application of AI methodologies, addressing challenges and exploring new opportunities in artificial intelligence.

Scope: The journal covers a wide range of topics within the field of artificial intelligence, including:
Machine Learning: Algorithms, methodologies, and applications of machine learning techniques.
Knowledge Representation: Theories and frameworks for representing and reasoning with knowledge.
Natural Language Processing: Algorithms and systems for processing and understanding natural language.
Computer Vision: Techniques for visual perception, image recognition, and understanding.
Robotics: AI applications in robotic systems, automation, and autonomous agents.
Cognitive Modeling: Theoretical models and simulations of human cognition.
Ethics and AI: Ethical considerations, biases, and societal impacts of AI technologies.
AI Applications: Practical applications of AI in various domains such as healthcare, finance, transportation, and more.