Aleksej Logacjov
Papers
2
Total Citations
15
H-Index
2
About
Aleksej Logacjov is a researcher at the intersection of robotics, lifelong machine learning, and human-robot interaction. His work addresses a fundamental challenge in artificial intelligence: how robots can continuously acquire new knowledge without forgetting what they have already learned—a problem known as catastrophic forgetting. In his most-cited paper, "Learning Then, Learning Now, and Every Second in Between," Logacjov explores lifelong learning frameworks for simulated humanoid robots, demonstrating how agents can adapt incrementally over extended interactions. This work has garnered 10 citations and contributes to the broader goal of creating robots capable of long-term autonomy. Logacjov also investigates the role of embodiment in learning, as seen in his study comparing virtual and physical social robots teaching a fictional language through a Game of Thrones-inspired role-playing game. This research, with 5 citations, highlights how engagement and physical presence affect knowledge transfer. By blending machine learning theory with applied robotics, Logacjov is helping to build machines that learn not just once, but continuously, throughout their operational lives.
Research Focus
Key Achievements
Top Papers
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