Cansu Sancaktar

Researching Curiosity in Artificial Agents 🤖
Currently based in TĂĽbingen, Germany

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I’m a PhD student at the Max Planck Institute for Intelligent Systems, supervised by Prof. Georg Martius. My research focuses on curiosity and intrinsically-motivated Reinforcement Learning (RL).

Taking inspiration from developmental psychology, I’m developing methods to help robots explore their environment efficiently without extrinsic rewards, similar to how children perform free play.

Before starting my PhD, I completed my Bachelor’s and Master’s degrees in Electrical Engineering and Information Technology at TU Munich. My specialization was in Robotics and Automation. During my studies, I worked on various machine learning projects spanning diverse fields such as robotics, signal processing, communications and neuroscience.

selected publications

2024

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    SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models
    Cansu Sancaktar*, Christian Gumbsch*, Andrii Zadaianchuk, and 2 more authors
    In The Training Agents with Foundation Models Workshop at RLC, 2024
    * indicates equal contribution

2023

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    Regularity as Intrinsic Reward for Free Play
    Cansu Sancaktar, Justus Piater, and Georg Martius
    In Advances in Neural Information Processing Systems (NeurIPS), 2023

2022

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    Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation
    Cansu Sancaktar, Sebastian Blaes, and Georg Martius
    In Advances in Neural Information Processing Systems (NeurIPS), 2022