IASC Open Access

Intelligent Automation & Soft Computing

https://www.techscience.com/iasc/special_detail/knowledge-guided-soft-computing 

Summary

Recent advances in artificial intelligence and intelligent automation have enabled significant progress in prediction, optimization, autonomous operations, and decision-making. However, many data-driven models still face challenges in handling uncertainty, adapting to dynamic environments, incorporating domain expertise, and providing interpretable decisions. These limitations can affect the reliability, efficiency, and trustworthiness of intelligent automation systems in real-world applications.

This Special Issue focuses on knowledge-guided soft computing for adaptive intelligent automation and decision-making. It aims to bring together innovative research integrating domain knowledge, fuzzy logic, expert systems, Bayesian reasoning, evolutionary optimization, and hybrid machine learning approaches to develop adaptive, reliable, and interpretable automation systems. Particular emphasis is placed on uncertainty-aware decision-making, intelligent control, context-aware automation, and knowledge-driven optimization in dynamic environments.

The Special Issue welcomes original research articles, methodological innovations, and practical applications demonstrating how knowledge-guided soft computing improves decision quality, adaptability, computational efficiency, and operational reliability. Applications may include intelligent manufacturing, smart transportation, autonomous systems, environmental management, and resource optimization.

Topics of interest include, but are not limited to:
1. Knowledge-guided soft computing for intelligent automation.
2. Fuzzy logic and neuro-fuzzy systems for adaptive control.
3. Hybrid machine learning and knowledge-based decision-making.
4. Bayesian reasoning and uncertainty-aware automation.
5. Expert systems and rule-based intelligent control.
6. Evolutionary and swarm intelligence for automated optimization.
7. Knowledge-guided reinforcement learning for autonomous decision-making.
8. Explainable and trustworthy automated decision-making systems.
9. Adaptive scheduling and intelligent resource allocation.
10. Context-aware and edge-enabled intelligent automation.

Scope clarification: This Special Issue primarily focuses on adaptive automation, operational decision-making, and intelligent control rather than standalone object detection, image classification, or visual recognition. Studies incorporating computer vision are welcome when their primary contribution concerns knowledge-guided automation or decision-making.

Keywords

knowledge-guided soft computing, intelligent automation, adaptive decision-making, fuzzy logic, neuro-fuzzy systems, knowledge-based reasoning, uncertainty-aware AI, evolutionary optimization, intelligent control, explainable artificial intelligence