Mollie Hamilton
Papers
1
Total Citations
7
H-Index
1
About
Mollie Hamilton is a leading researcher in developmental robotics and computational cognitive science, with a focus on open-ended learning and goal-directed behavior. Her work bridges computational models and developmental experiments to understand how agents—both human and robotic—autonomously acquire diverse skills. In her highly cited 2018 paper, "Action-outcome contingencies as the engine of open-ended learning," Hamilton demonstrates how the detection of action-outcome relationships drives the emergence of flexible, goal-oriented behavior, drawing on insights from infant development. This research has significant implications for creating more adaptive artificial intelligence systems that can learn continuously without explicit programming. With 7 citations, her work is gaining traction in the fields of cognitive robotics and developmental psychology. Hamilton’s contributions are notable for integrating empirical evidence from infant learning with computational frameworks, offering a powerful lens for designing robots that can autonomously explore and master their environments. Her research stands at the forefront of understanding how open-ended learning can be engineered, making her a key voice in the future of autonomous skill acquisition.
Research Focus
Key Achievements
Top Papers
- 1