Anca Dragan

schoolUniversity of California - Berkeleybar_chart#3676 Global Rank

Total Papers

HCI Rank

#3676

Research Areas

Years Active

Recent Publications

Aligning Human and Robot Representations

To act in the world, robots rely on a representation of salient task aspects: for example, to carry a coffee mug, a robot may consider movement efficiency or mug orientation in its behaviour. However, if we want robots to act for and with people, their representations must not be just functional but also reflective of…

HRI '23CorrespondingGenerative AI (Text, Image, Music, Video) +2

SIRL: Similarity-based Implicit Representation Learning

When robots learn reward functions using high capacity models that take raw state directly as input, they need to both learn a representation for what matters in the task --- the task "features" --- as well as how to combine these features into a single objective. If they try to do both at once from input designed to…

HRI '233rd AuthorHuman Pose & Activity Recognition +1

Towards Modeling and Influencing the Dynamics of Human Learning

Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to underestimate a robot's inertia. Nevertheless, these models change and improve ove…

HRI '20CorrespondingBest PaperBrain-Computer Interface (BCI) & Neurofeedback +2

LESS is More: Rethinking Probabilistic Models of Human Behavior

Robots need models of human behavior for both inferring human goals and preferences, and predicting what people will do. A common model is the Boltzmann noisily-rational decision model, which assumes people approximately optimize a reward function and choose trajectories in proportion to their exponentiated reward. Wh…

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