Agentic AI for Responsive Computing Ref.No.SSTCRC2603
1. Introduction
With the help of dynamic environments, user behaviour, and contextual cues, the research will investigate how to incorporate the principles of Agentic Artificial Intelligence (AI) into responsive computing systems. Agentic AI systems have goal-directed autonomy, which enables them to take action, make decisions, and continuously learn from interactions—in contrast to traditional AI systems that respond passively to inputs.
Emerging demands in intelligent user interfaces, autonomous robotics, smart environments, and adaptive healthcare systems are driving this project. The practical application of agentic AI frameworks in real-time, responsive computing environments has received little attention, despite the fact that intelligent agents and reinforcement learning have been the subject of numerous studies conducted independently.
2. Research Progress
-Literature review on agentic AI paradigms and responsive computing systems completed.
-Initial system design drafted using a modular architecture integrating Large Language Models (LLMs).
-Prototype under development for a smart healthcare assistant that self-adjusts based on patient status.
-Benchmark datasets identified for evaluation.
Next steps:
-Implementation of interaction loops with agentic behaviour simulation.
-Integration with real-world data collection environments.
-Pilot testing and model fine-tuning for dynamic response accuracy.
3. Cooperation Required
-Access to diverse sensor datasets and responsive environments (e.g., smart home/office labs).
-Collaboration with experts in human-computer interaction (HCI), cognitive AI, and cyber-physical systems.
-Funding support for computational infrastructure and pilot deployment.
-Institutional partnerships for field testing and user feedback collection.
4. Benefits
-The project will pioneer new ways in which machines perceive, adapt, and proactively assist users in real-time.
-Enhanced decision-making systems in critical sectors such as healthcare, smart mobility, and education.
-Advancement in the design of autonomous agents capable of social and environmental responsiveness.
-Potential applications in personalized care, disaster response systems, and sustainable energy management.
5. Outputs
-An open-source software toolkit for agentic behavior modeling and simulation in responsive environments (published on GitHub with documentation).
-Joint research proposal submission for larger research grants.
-Joint 3–4 Scopus/SCI-indexed journal papers on agentic AI architectures and applications.
-Joint 2 international conference presentations/workshops.
-Joint 1 patent on a hybrid agentic AI framework for responsive environments.
-Workshops or webinars for academia and industry to showcase project tools and promote adoption.