This issue presents a collection of contemporary research advancing the frontiers of artificial intelligence, machine learning, cybersecurity, healthcare informatics, and intelligent computational systems. The research addresses trustworthy and responsible AI for neurological disease detection, transformer-based EEG signal enhancement, AI-driven cybersecurity and digital forensics, privacy-preserving federated healthcare, model-free control, evolutionary intelligence, and game-theoretic learning. Further studies examine computational structure optimization, neural sequence modeling, reliability in retrieval-augmented generation agents, and multi-agent approaches to enterprise knowledge retrieval. Collectively, this issue highlights emerging methodologies that promote intelligent, secure, reliable, and practically applicable computational solutions across diverse domains.
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This issue presents a collection of research that explores intelligence as an adaptive, interactive, and autonomous capability. The articles in this issue span generative environment modeling, trustworthy distributed systems, human-computer interaction, embodied robotics, optimization, and learning under dynamic conditions. Despite their diverse applications, these contributions are united by a common objective: developing systems that can perceive complex environments, make informed decisions, and collaborate effectively with humans and other agents. Together, they illustrate the growing convergence of artificial intelligence, autonomous systems, and agent-based computing in addressing real-world challenges.