International Journal of Artificial Intelligence and Machine Learning (IJAIML)

Formerly the International Journal of Artificial Life Research (IJALR)
Editor(s)-in-Chief: Maki K. Habib (The American University in Cairo, Egypt)
Published: Continuous Volume
Copyright: ©2019
DOI: 10.4018/IJAIML
ISSN: 2642-1577
EISSN: 2642-1585

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Description

The International Journal of Artificial Intelligence and Machine Learning (IJAIML) provides a forum on the study of living systems intelligence, human level cognition and artificial systems, self-learning algorithms, and machines that exhibit intelligent autonomous behavioral characteristics. Additionally, it seeks to deliver the most up-to-date research on techniques, technologies and algorithms supporting machine learning. Presenting researchers and practitioners with access to explore the developments of bioinspired or human-like forms of systems, IJAIML promotes research in emerging disciplines of artificial life and machine learning to improve and comprehend real-world problems. This journal publishes all concepts, theories, systems, technologies and procedures that exhibit properties, phenomena, or abilities of any living system or human.

Volume 13, Issue 1

Volume 12, Issue 2

Volume 12, Issue 1

Volume 11, Issue 2

Volume 11, Issue 1

Volume 10, Issue 2

Volume 10, Issue 1

Volume 9, Issue 2

Volume 9, Issue 1

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Mission

The mission of the International Journal of Artificial Intelligence and Machine Learning (IJAIML) is to investigate the interdisciplinary hybrid nature involved in scientific, engineering, psychological, and social issues in synthetic life-like behavior and abilities. IJAIML publishes high-quality original research and review articles in theoretical and applied aspects of artificial intelligence and machine learning to address complex and dynamic issues in nature and demand complex information processing abilities to be emulated, recreated, and synthesized. Since computer and modeling form the basic tool in scientific research, the frontiers of computer and modeling connected with humanistic systems is one area of interest. The meaningful representation and manipulation of knowledge on computer of human intelligence and human language like the evolving development in soft computing, fuzzy sets, fuzzy logic, semantic networks, probabilistic and Bayesian reasoning, evidence theory, classical and mutli-value logic, and evolutionary operation with neural network and support vector machine are emphasized.