Paula Dornhofer Paro Costa
Papers
10
Total Citations
44
H-Index
4
About
Paula Dornhofer Paro Costa is a leading researcher at the intersection of cognitive robotics, developmental psychology, and human-robot interaction (HRI). Her work focuses on endowing robots with human-like learning and decision-making capabilities, drawing inspiration from Piagetian developmental theory and intrinsic motivation. Costa’s major contributions include the development of cognitive architectures that integrate curiosity, affect, and drive-based reinforcement learning, enabling robots to autonomously acquire complex behaviors and make long-term decisions in dynamic environments. Her most cited paper, “Piagetian experiments to DevRobotics” (2023, 9 citations), bridges developmental psychology and robotics, while “Curiosity and Affect-Driven Cognitive Architecture for HRI” (2025, 6 citations) explores how robots with different value systems can understand human needs. Costa also applies emotion recognition technologies to support children with Autism Spectrum Disorder, as seen in her 2019 paper (8 citations). Her work on procedural constructive learning and the Iowa Gambling Task for robots demonstrates a sustained commitment to creating autonomous agents that learn incrementally and ethically. With over 40 citations across her top publications, Costa is shaping the future of socially aware, cognitively plausible robots.
Research Focus
Key Achievements
Top Papers
- 1Piagetian experiments to DevRobotics9 citations · 2023
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- 3Curiosity and Affect-Driven Cognitive Architecture for HRI6 citations · 2025
- 4A motivational-based learning model for mobile robots6 citations · 2024
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- 9Learning over the Attentional Space with Mobile Robots2 citations · 2020
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