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ad91e86 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | # EvolvingNav Agent
## Code
| Path | Function |
| --- | --- |
| `src/readyagent/p4d_belief/` | Continuous-time history encoder and persistence–relocation belief |
| `evolvingnav_paper/memory.py` | Causal entity versions, RGB-D backprojection and evidence provenance |
| `evolvingnav_paper/transition_model.py` | Row-normalized chronological transition head |
| `evolvingnav_paper/filter.py` | Current-time belief, arrival forecasts and evidence rounds |
| `evolvingnav_paper/coverage.py`, `calibration.py` | Online depth coverage and validation-fitted detection probability |
| `evolvingnav_paper/agent.py`, `controller.py` | Event-driven actions and frozen VLM tool selection |
| `evolvingnav_paper/world.py`, `backend.py`, `run.py` | Habitat action adapter and benchmark runner |
| `scripts/` | Dataset packing, belief/transition training and calibration |
| `tests/` | Unit tests |
## Environment
Use Python 3.11 with Habitat-Sim 0.3.3 installed.
```bash
cd code
python -m pip install -r requirements.txt
export PYTHONPATH=.:src:scripts
export MAGNUM_LOG=quiet HABITAT_SIM_LOG=quiet
export P4D_DATASET=/absolute/path/to/p4d_hssd_30d_v0.6.0
export NAV_TASKS=/absolute/path/to/p4d_navigation_107734254_v1.0
export HSSD_ROOT=/absolute/path/to/hssd-hab
export NAVMESH_ROOT=/absolute/path/to/hssd-hab/navmeshes
```
## Train
If `records/packed/{train,val,test}.npz` are absent:
```bash
python scripts/pack_p4d_hssd_records.py --root "$P4D_DATASET"
```
Train the query-time belief and the chronological transition head:
```bash
python scripts/train_p4d_belief.py \
--dataset-root "$P4D_DATASET" --output runs/p4d_seed0 \
--seeds 0 --skip-classical
python scripts/train_transition.py \
--dataset "$P4D_DATASET" \
--belief-checkpoint runs/p4d_seed0/checkpoints/p4d/seed_0/best.pt \
--output runs/transition_seed0
```
Collect held-out RGB-D validation observations and fit detector calibration:
```bash
python scripts/collect_calibration.py \
--dataset "$P4D_DATASET" --tasks "$NAV_TASKS" \
--hssd-root "$HSSD_ROOT" --navmesh-root "$NAVMESH_ROOT" \
--limit 8 --output runs/calibration_val.jsonl
python scripts/fit_calibration.py \
--validation-jsonl runs/calibration_val.jsonl \
--output runs/detection_calibration.json
```
## Run
Run the event-driven N3 Agent with Grounding DINO + SAM2:
```bash
python -m evolvingnav_paper.run \
--task n3 --world static --limit 10 \
--dataset "$P4D_DATASET" --tasks "$NAV_TASKS" \
--hssd-root "$HSSD_ROOT" --navmesh-root "$NAVMESH_ROOT" \
--checkpoint runs/p4d_seed0/checkpoints/p4d/seed_0/best.pt \
--calibration runs/detection_calibration.json \
--output runs/n3_static_10
python -m evolvingnav_paper.verify_visual runs/n3_static_10 \
--tasks "$NAV_TASKS" --hssd-root "$HSSD_ROOT" \
--navmesh-root "$NAVMESH_ROOT"
```
Add `--controller luna` and set `OPENAI_API_KEY` to use the frozen GPT-5.6-Luna tool controller. Model IDs and revisions for Grounding DINO and SAM2 are in `configs/perception.yaml`.
For an N4 task directory with `public/episodes_n4.jsonl`, each private `target_motion_schedule` event supplies seconds after query (`time_s`), `target_position_xyz`, `current_state_id`, and `valid_goal_viewpoints`:
```bash
python -m evolvingnav_paper.run \
--task n4 --world routine --limit 2 \
--dataset "$P4D_DATASET" --tasks /absolute/path/to/n4_tasks \
--hssd-root "$HSSD_ROOT" --navmesh-root "$NAVMESH_ROOT" \
--checkpoint runs/p4d_seed0/checkpoints/p4d/seed_0/best.pt \
--transition-checkpoint runs/transition_seed0/best.pt \
--output runs/n4_routine_2
```
Every run writes `policy.jsonl`, `scores.jsonl` and `summary.json` to a new output directory.
## Tests
```bash
python -m pytest tests -q
```
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