# Adam: An Embodied Causal Agent in Open-World Environments

Shu Yu1, 2, Chaochao Lu2,†
1Fudan University 2Shanghai Artificial Intelligence Laboratory
†Corresponding author.
arXiv Code
The causal graph learned in lifelong learning.
Adam successfully unlocks all 41 actions we implement and discovers accurate causal relationships.

## Abstract

## mineDiamondOre

## gatherWoodLog

## gatherStone

## smeltRawIron

## Automatic exploration

## Components

## Environmental awareness

## Causal graph learning

## Task executing

## Performance

## Interpretability

## Efficiency

## Robustness

## Conclusion

## BibTeX

    @article{yu2024adam,
      title   = {ADAM: An Embodied Causal Agent in Open-World Environments},
      author  = {Shu Yu and Chaochao Lu},
      year    = {2024},
      journal = {arXiv preprint arXiv:2410.22194}
    }