Welcome to Volume 1, Issue 1 of the Journal of Artificial Intelligence Research (JAIR). Our inaugural issue presents a pioneering study titled "Reinforcement Learning Algorithms: Conducting a Comparative Analysis," providing insights into the strengths and weaknesses of various algorithms. Authored by Rajeev Ranjan, this research sets the stage for informed decision-making in AI. As we embark on this journey, we invite readers to explore the diverse landscape of artificial intelligence. While this volume showcases one exceptional contribution, we eagerly anticipate future issues featuring a breadth of topics and perspectives. We extend our gratitude to contributors, reviewers, and readers for their support in realizing JAIR's vision. Thank you for joining us at the forefront of AI research.
Journal Name: Journal of Artificial Intelligence Research (JAIR)
Impact Factor: 4.6 (By ResearchBib)
h-index: 15 (By Google Scholar)
i10-index: 22 (By Google Scholar)
Journal Initials: JAIR
Publication Mode: Digital
Frequency: Semi-Annual (2 Issues a year)
Launch Year: 2021
Review Mode: Double Blind Peer Review
Plagiarism Allowed: 10% (as per Turnitin)
Coverage: Worldwide
Language: English
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The Journal of Artificial Intelligence Research (JAIR) is a peer-reviewed, open-access journal that publishes original research articles, reviews, and short communications in all areas of science and technology. The journal welcomes submissions from all researchers, regardless of their geographic location or institutional affiliation.
Journal of Artificial Intelligence Research (JAIR)
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