Sarah Rainge

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About

Sarah Rainge is a researcher whose work sits at the intersection of artificial intelligence, robotics, and educational technology. Her primary research areas include reinforcement learning, declarative programming, and the development of accessible human-robot interaction tools. Rainge’s most significant contribution is her pioneering approach to integrating reinforcement learning with declarative programming to enable autonomous agents to learn causal laws in dynamic, real-world domains—a foundational step toward more interpretable and adaptable AI systems. Her 2014 paper on this topic has garnered 6 citations, reflecting its niche but growing influence in the AI planning community. Rainge is also the creator of DOROTHY, a novel educational tool that extends the Alice 3D programming environment to support bidirectional communication between users and autonomous robots. DOROTHY allows individuals with no prior programming experience to quickly design graphical routines and control robotic systems, making her work notable for its emphasis on lowering barriers to entry in robotics education. Through these contributions, Rainge has advanced both the theoretical underpinnings of causal learning in AI and the practical accessibility of robotic programming for novice users.