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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.

Repository Paper
choreographer Choreographer: Learning and Adapting Skills in Imagination [website] [arxiv]
mastering-urlb Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels [website] [arxiv]
contrastive-aif Contrastive Active Inference [website] [arxiv]
lbs-exploration Curiosity-Driven Exploration via Latent Bayesian Surprise [website] [arxiv]

Popular repositories

  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 27 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 27 5

  3. vue-graph-vis vue-graph-vis Public

    A Vue component to render graphs on canvas, based on Vis.js

    Vue 4

  4. vime-pytorch vime-pytorch Public

    PyTorch implementation of the VIME paper (Variational Information Maximizing Exploration)

    Python 4 2

  5. contrastive-aif contrastive-aif Public

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

    Python 3 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