# docs/ Index

Documentation and report artefacts for the DTS307TC PPO coursework.

## Final deliverables

| File | Purpose |
|------|---------|
| `CW1_REPORT_TEMPLATE.docx` | Pre-formatted Word source. IEEE style (11pt Times New Roman, 1.15 spacing, 2.5cm margins). All numbers, figures, and native equations embedded. The student fills in cover-page details and exports to PDF. |
| `generate_report_template.py` | Source script that produces the template. |

**Word count** (excluding References and Appendix): 2972 / 3000.

## Figures referenced in the report

| File | Used in | Description |
|------|---------|-------------|
| `fig_architecture.png` | Fig. 1 | Shared-CNN actor-critic architecture (1.69M params) |
| `fig_training_curves.png` | Fig. 2 | 6-panel training curves over 1.5M steps |
| `fig_eval_bar.png` | Fig. 3 | Per-episode evaluation returns on 20 unseen seeds |
| `fig_sb3_comparison.png` | Fig. 4 | Ours vs SB3 baseline diagnostics overlay |
| `demo.mp4` | Submitted alongside the zip | 25-second video of the trained agent on seed 117 (return 925.40, completed at wrapped step 187) |

## Numerical evidence

| File | Content |
|------|---------|
| `eval_summary.json` | 20-episode evaluation of `models/ppo_final.pt`. Mean 830.17 ± 104.79; min 436.81; max 914.90 |
| `eval_summary_sb3.json` | 20-episode evaluation of the SB3 baseline. Mean 664.32 ± 173.93; min 309.40; max 857.14 |
| `checkpoint_scan_vec_main_v3.json` | Per-checkpoint evaluation table; basis for selecting `iter_0700.pt` as the submitted model |

## Cross-cutting documents

| File | Content |
|------|---------|
| `development_log.md` | Step-by-step development timeline (Days 1-9) |
| `issues_and_fixes.md` | Three substantive engineering challenges resolved + three documented negative-result ablations (raw material for Section 3.4 and 4.4) |
| `submission_checklist.md` | Pre-submission verification checklist |
| `INDEX.md` | This file |

## Project state at submission

```
runs/      vec_main_v3/         main 1.5M-step training
           sb3_baseline/run_1/  SB3 baseline 500K reference

models/    ppo_final.pt          submitted agent (= iter_0700.pt selected
                                 by held-out checkpoint scanning)
           vec_main_v3/final.pt  training-end backup
           sb3_baseline/final.zip SB3 reference

src/       eight Python modules, no SB3 imports
notebooks/ three development notebooks (env exploration, network sanity,
           evaluation)
```