Samyukta Yagati

Papers

Total Citations

123

H-Index

About

Samyukta Yagati is a cognitive scientist whose research illuminates how the human mind structures complex problems for efficient decision-making. Her work centers on the computational principles underlying hierarchical planning and representation learning—exploring how people spontaneously organize environments into nested clusters of states, enabling them to break daunting tasks into manageable sub-problems. Yagati’s seminal 2020 paper, “Discovery of hierarchical representations for efficient planning,” has garnered 107 citations, establishing her as a leading voice in understanding the cognitive architecture that supports flexible, multi-level reasoning. This work demonstrates that humans do not simply react to stimuli but actively construct abstract representations that compress experience into actionable chunks—a mechanism that may underpin everything from everyday navigation to expert problem-solving. Her 2018 precursor to this study, with 16 citations, laid the groundwork for these insights. Yagati’s contributions bridge cognitive psychology and artificial intelligence, offering a blueprint for building more human-like planning algorithms. For students and researchers, her findings challenge us to rethink how we learn, represent, and solve problems—suggesting that the key to tackling complexity lies not in brute force, but in the elegant discovery of structure.