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ttpd-weights

Reinforcement Learning
operations-research
vehicle-routing
combinatorial-optimization
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Publish TTP-D artifacts

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  1. README.md +56 -0
  2. a280/gat/benchmark-tuned/n10/best.pt +3 -0
  3. a280/gat/benchmark-tuned/n100/best.pt +3 -0
  4. a280/gat/benchmark-tuned/n15/best.pt +3 -0
  5. a280/gat/benchmark-tuned/n20/best.pt +3 -0
  6. a280/gat/benchmark-tuned/n30/best.pt +3 -0
  7. a280/gat/benchmark-tuned/n40/best.pt +3 -0
  8. a280/gat/benchmark-tuned/n5/best.pt +3 -0
  9. a280/gat/benchmark-tuned/n50/best.pt +3 -0
  10. a280/gat/sampled/n15/best.pt +3 -0
  11. a280/gat/sampled/n15/best_milp.pt +3 -0
  12. a280/gat/sampled/n20/best.pt +3 -0
  13. a280/gat/sampled/n20/best_milp.pt +3 -0
  14. a280/gat/specialists/n10.pt +3 -0
  15. a280/gat/specialists/n15.pt +3 -0
  16. a280/gat/specialists/n20.pt +3 -0
  17. a280/gat/specialists/n5.pt +3 -0
  18. a280/lisa/bc-initial/n5_n10.pt +3 -0
  19. a280/lisa/bc/n100.pt +3 -0
  20. a280/lisa/bc/n15.pt +3 -0
  21. a280/lisa/bc/n20.pt +3 -0
  22. a280/lisa/bc/n30.pt +3 -0
  23. a280/lisa/bc/n40.pt +3 -0
  24. a280/lisa/bc/n50.pt +3 -0
  25. a280/lisa/bc/n5_n10.pt +3 -0
  26. a280/lisa/gat-n50/best.pt +3 -0
  27. a280/lisa/gat-n50/last.pt +3 -0
  28. a280/mlp/benchmark-tuned/n10/best.pt +3 -0
  29. a280/mlp/benchmark-tuned/n100/best.pt +3 -0
  30. a280/mlp/benchmark-tuned/n15/best.pt +3 -0
  31. a280/mlp/benchmark-tuned/n20/best.pt +3 -0
  32. a280/mlp/benchmark-tuned/n30/best.pt +3 -0
  33. a280/mlp/benchmark-tuned/n40/best.pt +3 -0
  34. a280/mlp/benchmark-tuned/n5/best.pt +3 -0
  35. a280/mlp/benchmark-tuned/n50/best.pt +3 -0
  36. a280/mlp/sampled/n20/best.pt +3 -0
  37. a280/mlp/sampled/n20/best_milp.pt +3 -0
  38. manifest.json +287 -0
  39. ttd300/gat/benchmark-tuned/n10/best.pt +3 -0
  40. ttd300/gat/benchmark-tuned/n10/last.pt +3 -0
  41. ttd300/gat/benchmark-tuned/n100/best.pt +3 -0
  42. ttd300/gat/benchmark-tuned/n100/last.pt +3 -0
  43. ttd300/gat/benchmark-tuned/n20/best.pt +3 -0
  44. ttd300/gat/benchmark-tuned/n20/last.pt +3 -0
  45. ttd300/gat/benchmark-tuned/n30/best.pt +3 -0
  46. ttd300/gat/benchmark-tuned/n30/last.pt +3 -0
  47. ttd300/gat/benchmark-tuned/n40/best.pt +3 -0
  48. ttd300/gat/benchmark-tuned/n40/last.pt +3 -0
  49. ttd300/gat/benchmark-tuned/n50/best.pt +3 -0
  50. ttd300/gat/benchmark-tuned/n50/last.pt +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - operations-research
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+ - vehicle-routing
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+ - reinforcement-learning
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+ - combinatorial-optimization
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+ ---
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+
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+ # TTP-D solver weights
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+
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+ Trained checkpoints for the Travelling Thief Problem with Drone (TTP-D) study.
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+ Benchmark instances and result tables live in the companion dataset repo
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+ [`Murjani/ttpd-benchmarks`](https://huggingface.co/datasets/Murjani/ttpd-benchmarks); the code is at
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+ https://github.com/Kcbir/ttpd.
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+
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+ ## Layout
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+
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+ ```
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+ <variant>/<model>/<family>/n<N>/best.pt
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+ ```
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+
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+ - **variant** — `a280` (fixed drone endurance) or `ttd300` (endurance-conditioned)
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+ - **model** — `gat` (attention encoder), `mlp` (the encoder ablation), `lisa`
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+ (behaviour cloning)
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+ - **family** — what the policy was trained on:
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+
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+ | family | trained on | use it for |
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+ |---|---|---|
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+ | `benchmark-tuned/` | the five benchmark instances of that size | the headline results |
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+ | `sampled/` | randomly sampled a280 subsets | generalisation; warm start for the above |
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+ | `specialists/` | early small-n runs | the n<=20 rows using a dedicated small model |
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+
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+ LISA weights live at `<variant>/lisa/bc/n<N>.pt`, with
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+ `a280/lisa/bc-initial/` and `a280/lisa/gat-n50/` kept for provenance.
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+
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+ `best.pt` is the deliverable (best held-out beam evaluation); `last.pt` is a
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+ resume artifact; `best_milp.pt` is selected by MILP gap instead of eval return.
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+
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+ ## Loading
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+
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+ Checkpoints are `torch.save` payloads with a `"policy"` state-dict key:
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+
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+ ```python
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+ import torch
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+ from huggingface_hub import hf_hub_download
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+
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+ path = hf_hub_download("Murjani/ttpd-weights", "a280/gat/bench-tuned/n30/best.pt")
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+ payload = torch.load(path, map_location="cpu", weights_only=False)
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+ policy.load_state_dict(payload["policy"])
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+ ```
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+
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+ The repo code resolves these automatically -- see `ttpd_hub.ensure_local`.
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+
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+ `manifest.json` records, for every file, the path it was published from and its
56
+ sha256.
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