Justin Karneeb

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About

Justin Karneeb is a researcher whose work lies at the intersection of artificial intelligence, robotics, and autonomous systems, with a particular focus on goal reasoning and behavior recognition. His most influential contribution is the development of **Iterative Goal Refinement for Robotics**, a framework that models how autonomous agents dynamically select and adjust their goals in response to notable events. This work, which has garnered 13 citations, addresses a critical challenge in robotics: enabling actors to assume responsibility for their own goal selection rather than relying on static, pre-defined objectives. Karneeb’s approach treats goal reasoning as an iterative process, where abstract constraints are progressively refined to guide decision-making in complex, dynamic environments. In a second highly cited paper (12 citations), he applied **case-based behavior recognition** to beyond-visual-range air combat, demonstrating how unmanned aerial vehicles (UAVs) can intelligently interpret hostile agent behaviors to plan effectively in mixed human-robot teams. This work has significant implications for military and aerospace applications, where real-time, adaptive planning is essential. Karneeb’s research is notable for bridging theoretical models of reasoning with practical, high-stakes scenarios, making him a key figure in advancing autonomous decision-making.