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mazpie/README.md

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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  1. 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 …

    Python 30 5

  2. 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.

    Python 30 6

  3. genrl genrl Public

    [GenRL] Multimodal foundation world models allow grounding language and video prompts into embodied domains, by turning them into sequences of latent world model states. Latent state sequences can …

    Python 30

  4. 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 12

  5. contrastive-aif contrastive-aif Public

    [NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.

    Python 8 1

  6. lbs-exploration lbs-exploration Public

    [AAAI-22] Curiosity-based objective for exploration with reinforcement learning in state-based and vision-based environments.

    Python 1