AI-Planning / AI-Planning/macq
Bonet & Geffner (ECAI'20, arXiv'21)
Open
acquisition-technique
- Dominant language
- Python
- Stars
- 25
- Forks
- 6
- PR merge metrics
- No merged PRs in 30d
Description
## Notes
- Just takes state IDs and transitions as input
- Produces lifted representation, and does so using SAT
- Second one seems to improve on the first, and does so using ASP
- We may want to stick with the first initially
## References
- [ ] [Learning First-Order Symbolic Representations for Planning from the Structure of the State Space](https://arxiv.org/abs/1909.05546)
- [ ] [Learning First-Order Representations for Planning from Black-Box States: New Results](https://arxiv.org/abs/2105.10830)
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