Giulia Sajeva
Papers
3
Total Citations
12
H-Index
2
About
Giulia Sajeva is a pioneering researcher in autonomous robotics, with a career focused on bridging symbolic reasoning and behavioral processing in artificial agents. Her most influential work, "An architecture for autonomous agents integrating symbolic and behavioral processing" (2002, 7 citations), introduced a novel framework that uses conceptual space representations to connect high-level symbolic reasoning with low-level sensorimotor data. This integration allows robots to move beyond reactive behaviors and engage in more deliberate, context-aware decision-making—a foundational contribution to hybrid AI architectures. Earlier, Sajeva explored neural network approaches for action representation, as seen in her 1997 paper on ASSOM networks (3 citations), which modeled how agents can learn and categorize behaviors. She also applied her expertise to cultural heritage robotics, using simulation-based planning and mobile devices to enhance robotic interaction with historical sites (2004, 2 citations). Though her citation counts are modest, Sajeva’s work represents an important step in creating more intelligent, adaptable autonomous systems, particularly in environments requiring both perception and planning.
Research Focus
Key Achievements
Top Papers
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