International Journal of Reasoning-based Intelligent Systems Inderscience Publishers Impact Factor

International Journal of Reasoning-based Intelligent Systems - Inderscience | 2024 Cite Score:1.1 | Q4

International Journal of Reasoning-based Intelligent Systems With Cite Score

Cite Score and Journal Rank of International Journal of Reasoning-based Intelligent Systems

About: International Journal of Reasoning-based Intelligent Systems (IJRIS) is a peer-reviewed academic journal dedicated to the study and development of intelligent systems that utilize reasoning as a core component. The journal provides a platform for the dissemination of research on advanced reasoning techniques and their applications in various domains, contributing to the broader field of artificial intelligence.
Objective: The primary objective of the International Journal of Reasoning-based Intelligent Systems is to advance the understanding and application of reasoning processes in intelligent systems. The journal covers a wide range of topics, including logic-based reasoning, rule-based systems, expert systems, decision support systems, knowledge representation, and automated reasoning. It aims to publish research that enhances the design, implementation, and evaluation of reasoning-based systems that can solve complex problems across different industries and sectors.
Interdisciplinary Approach: The journal adopts an interdisciplinary approach by integrating research from various fields such as artificial intelligence, computer science, cognitive science, mathematics, and engineering. This approach allows for a comprehensive exploration of reasoning-based techniques and their applications, from theoretical foundations to practical implementations. Contributions that bridge these disciplines and provide new insights into the role of reasoning in intelligent systems are particularly encouraged.
Impact and Significance: The International Journal of Reasoning-based Intelligent Systems has a significant impact on both the academic and professional communities involved in the development of intelligent systems. The research published in the journal contributes to the advancement of reasoning technologies, offering valuable insights and practical solutions that enhance the capabilities of intelligent systems. It serves as a key resource for researchers, developers, and practitioners who are focused on creating and applying reasoning-based systems in various domains such as healthcare, finance, robotics, and more.

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Editor-in-Chief: Prof. Jair Minoro Abe

Scope: The International Journal of Reasoning-based Intelligent Systems is a scholarly publication that focuses on the research and development of intelligent systems driven by reasoning techniques. This journal covers a broad spectrum of topics related to reasoning methodologies, intelligent systems, and their applications in various domains. The key areas of interest include:
1. Reasoning Techniques and Algorithms: Research on new reasoning methods, algorithms, and frameworks that enhance the capabilities of intelligent systems. This includes deductive, inductive, abductive, and probabilistic reasoning approaches.
2. Knowledge Representation and Reasoning: Studies on how knowledge is represented and processed in intelligent systems. Topics include ontologies, logic programming, semantic networks, and other methods that support reasoning.
3. Automated Reasoning: Exploration of automated reasoning systems, including theorem proving, model checking, and constraint satisfaction problems (CSP) that aid in decision-making processes.
4. Reasoning under Uncertainty: Research on methods for reasoning in environments where information is incomplete, inconsistent, or uncertain. This includes Bayesian networks, fuzzy logic, and belief networks.
5. Cognitive and Computational Reasoning: Studies that explore the intersection of cognitive science and artificial intelligence, focusing on how computational models can mimic human reasoning and decision-making processes.
6. Intelligent Decision Support Systems: Development of reasoning-based decision support systems (DSS) that assist humans in making complex decisions by providing reasoning capabilities and actionable insights.
7. Machine Learning and Reasoning Integration: Research on the integration of machine learning techniques with reasoning systems to enhance the performance and adaptability of intelligent systems.
8. Multi-Agent Reasoning: Studies on reasoning mechanisms within multi-agent systems, including negotiation, cooperation, and conflict resolution among autonomous agents.
9. Reasoning for Natural Language Processing: Exploration of reasoning methods applied to natural language understanding, text mining, and semantic interpretation in intelligent systems.
10. Reasoning in Robotics and Autonomous Systems: Research on reasoning techniques used in robotics, including planning, perception, and decision-making in autonomous systems.
11. Ethical Reasoning in AI Systems: Studies that address the ethical considerations and challenges of implementing reasoning in AI systems, including fairness, accountability, and transparency.
12. Applications of Reasoning-based Systems: Real-world applications of reasoning-based intelligent systems in areas such as healthcare, finance, cybersecurity, manufacturing, and more.