The objective of my research is to build intelligent agents that discover and learn how to behave in the environment by interacting with it.
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Qualcomm AI Research
- Amsterdam, Netherlands
- https://mazpie.github.io/
- @pietromazzaglia
- https://scholar.google.ca/citations?user=c-PYVTgAAAAJ&hl=en
Highlights
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choreographer
choreographer Public[ICLR 2023] Choreographer: a model-based agent that discovers and learns unsupervised skills in latent imagination, and it's able to efficiently coordinate and adapt the skills to solve downstream …
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mastering-urlb
mastering-urlb Public[ICML 2023] Pre-train world model-based agents with different unsupervised strategies, fine-tune the agent's components selectively, and use planning (Dyna-MPC) during fine-tuning.
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redundancy-action-spaces
redundancy-action-spaces Public[RA-L 2024] Novel action spaces leveraging redundancy in 7 DoF arms enable efficient & precise learning in robotic manipulation
Python 16
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contrastive-aif
contrastive-aif Public[NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.
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lbs-exploration
lbs-exploration Public[AAAI-22] Curiosity-based objective for exploration with reinforcement learning in state-based and vision-based environments.
Python 3
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