Summary of Adam: An Embodied Causal Agent in Open-world Environments, by Shu Yu et al.
ADAM: An Embodied Causal Agent in Open-World Environments
by Shu Yu, Chaochao Lu
First submitted to arxiv on: 29 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces ADAM, an embodied causal agent that can learn structured knowledge in open-world environments like Minecraft. Existing agents struggle with continuous learning due to the opacity of black-box models and excessive reliance on prior knowledge during training. To overcome these challenges, ADAM is equipped with four key components: interaction, causal model, controller, and perception modules. The causal model module constructs an ever-growing causal graph from scratch, enhancing interpretability and reducing reliance on prior knowledge. Extensive experiments demonstrate that ADAM builds a nearly perfect causal graph, enabling efficient task decomposition and execution with strong interpretability. Notably, ADAM maintains its performance in modified Minecraft games without prior knowledge, showing remarkable robustness and generalization capability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating an artificial intelligence agent called ADAM that can learn new things on its own in a video game like Minecraft. The problem is that current AI agents are not very good at learning new things because they rely too much on what they already know. To solve this, the researchers created ADAM with four special parts: one for interacting with the environment, one for figuring out how things work together, one for making decisions, and one for seeing and understanding what’s happening. The results show that ADAM is very good at learning new things and can even do it without any prior knowledge. |
Keywords
» Artificial intelligence » Generalization
