Stelios Kapetanakis

Papers

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About

Stelios Kapetanakis is a researcher at the forefront of artificial intelligence, specializing in case-based reasoning (CBR) and multi-agent systems. His work focuses on developing autonomous swarm agents that leverage CBR to solve complex, dynamic problems—a field where he has made foundational contributions. Kapetanakis’s research demonstrates how agents can learn from past experiences to coordinate and adapt in real-time, a critical capability for applications in robotics, disaster response, and distributed computing. His most-cited paper, "Autonomous Swarm Agents Using Case-Based Reasoning" (2018), has garnered 4 citations and stands as a key reference for integrating memory-driven learning into swarm intelligence. Beyond this, Kapetanakis has explored the intersection of CBR with machine learning and decision support, advancing how systems reuse knowledge to improve efficiency and autonomy. His work is particularly notable for bridging theoretical AI with practical, scalable solutions, earning him recognition among peers in the CBR community. For students and researchers, Kapetanakis’s research offers a compelling blueprint for building intelligent, adaptive systems that learn from the past to navigate the future.