9th International Workshop on Advances in Artificial Intelligence and Machine Learning (AIML 2026): AI for Proactive and Responsible Autonomy: Innovations, Insights, and Applications

Goals of the Workshop

The goal of the workshop, ninth in the series at COMPSAC, is to foster interaction and information exchange among AI researchers and practitioners from academia and industry, on the safe, reliable and trustworthy application of Artificial Intelligence (AI) and Machine learning (ML) in real-world applications.

Workshop Theme 

The increasing autonomy and decision-making capabilities of AI systems are creating a paradigm shift from reactive intelligence to proactive and responsible intelligence systems. Future AI systems are expected to anticipate needs, adapt dynamically to the context, and make autonomous and responsible decisions with awareness of ethical, social, and human implications. The workshop on AI for Proactive and Responsible Autonomy: Innovations, Insights, and Applications’ at IEEE COMPSAC 2026 aims to explore cutting-edge research, frameworks, and real-world applications that empower AI systems to evolve from task-driven automation to agentic intelligence. The workshop seeks to create a platform for academia, industry, and policymakers to exchange ideas, foster collaboration, and advance the understanding of how proactive and responsible autonomy can transform domains such as robotics, healthcare, transportation, cybersecurity, smart cities, and digital ecosystems. It encourages discussions around architectures, algorithms, human-centered design principles, and governance mechanisms that enable AI to act with foresight, transparency, and accountability. At the same time, the workshop addresses the equally critical dimension of responsible autonomy—ensuring that proactive systems operate with transparency, fairness, explainability, and adherence to ethical and safety norms. Contributions that explore computational trust, responsibility-by-design frameworks, and human-AI collaboration models are also encouraged.

Scope of the Workshop 

This workshop will facilitate much needed interaction and information exchange among AI researchers, practitioners and business executives. It will provide an interactive forum for discussion on recent and ongoing developments, key issues and challenges, and practices related to AI applications. It will also serve as a platform to present case studies and discuss application to experience as well as to demonstrate applications and AI tools. Researchers and practitioners from all over the world, from academia, industry, and government will be invited to present their work and perspectives and participate in the workshop.  Participants will gain insights into the strategies and tools that will drive the development of AI and ML towards a more autonomous, adaptive, and ethically aware future.

Topics of interest include, but are not limited to: 

• Advances in AI and machine learning, deep learning, cognitive computing,
  intelligent agent, chatbots
• Foundations and Theories of Proactive Autonomy
• Computational frameworks for agentic and anticipatory AI
• Temporal and causal models for foresight and planning
• Machine Learning Paradigms for Proactive Systems
• Multi-task and transfer learning for dynamic environments
• Uncertainty quantification and risk-aware decision making
• Mechanisms for interpretability in proactive decision-making
• Formal verification and safety assurance of autonomous agents
• Human-in-the-loop architectures
• Multi-agent coordination and emergent behavior modelling
• Real-time situational awareness and intent-based control systems
• Autonomous mobility, robotics, and swarm intelligence
• Metrics for proactivity, autonomy, and trustworthiness
• Frameworks for auditing, explainability, and compliance in autonomous systems
• Proactive healthcare monitoring and precision medicine
• Cybersecurity systems with predictive and adaptive defense
• Defense and mission-critical systems with proactive threat response
• AutoML models
• Casual ML models
• Self-repairing and resilient intelligent systems