Ferdian Pratama
Papers
3
Total Citations
15
H-Index
3
About
Ferdian Pratama is a researcher at the forefront of cognitive robotics, specializing in memory-inspired architectures for long-term human-robot interaction. His work bridges artificial intelligence and neuroscience by designing systems that enable robots to acquire, store, and recall knowledge over extended periods using contextual cues. Pratama’s key contribution is the development of an integrated epigenetic robot architecture, where a context-influenced Long-Term Memory organizes information flow between working and long-term memory components. This framework, detailed in his most-cited paper (2014, 7 citations), moves beyond conventional machine learning by emphasizing continuous, context-driven knowledge acquisition—a critical step toward more adaptive and socially intelligent robots. His subsequent works (2016, 4 citations; 2015, 4 citations) extend this architecture to verbal interaction, demonstrating how robots can form and recall relevant perceptual traits during dialogue. Though his citation counts are modest, Pratama’s conceptual innovations are foundational for researchers tackling the challenge of lifelong learning in autonomous systems. His work is particularly notable for its interdisciplinary approach, drawing from human memory models to create robots that learn not just from data, but from the rich, contextual fabric of real-world interaction.
Research Focus
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Top Papers
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