| --- |
| tags: |
| - negotiation |
| - multi-agent |
| - game-theory |
| - bayesian-agents |
| - belief-accuracy |
| configs: |
| - config_name: episodes |
| data_files: |
| - split: train |
| path: episodes.csv |
| - config_name: cells |
| data_files: |
| - split: train |
| path: cells.csv |
| - config_name: belief_turns |
| data_files: |
| - split: train |
| path: belief_turns.csv.gz |
| --- |
| |
| # 2026.RA.Pure-Rounds-Sweep — does more negotiating time help a Bayesian table close? |
|
|
| Five automated negotiators must agree on one package out of 256. Each holds a private score sheet and a |
| private walk-away threshold; a deal needs all five to accept. This corpus sweeps the one thing the frozen |
| campaign never varied — **the number of negotiation rounds before the forced final vote** — across |
| 4 to 256 rounds, for the two lineups that contain no language model and therefore |
| cost only CPU: `all_rational` (five copies of a Bayesian agent that maintains a posterior over hypotheses |
| about each opponent's sheet) and `all_oracle` (five agents that are simply told every sheet). |
|
|
| **The headline: more time buys nothing.** Deal rate across deadlines 4 → 64 reads 0.233 / 0.267 / 0.208 / |
| 0.208 / 0.250 and normalized score 0.195 / 0.230 / 0.182 / 0.178 / 0.207, with every instance-clustered |
| interval overlapping every other. Rounds-to-agreement tracks the deadline almost exactly, so the agents use |
| the whole horizon and finish where they started. The mechanism is in `belief_turns.csv.gz`: belief accuracy |
| saturates by round 16, so extra rounds deliver no extra identification of opponents, and without |
| identification there is nothing to concede to. The omniscient arm closes 1.000 of games at every deadline, |
| confirming the horizon itself is not the constraint. Full analysis: **research note 0061** in the source repo. |
|
|
| ## What is in here |
|
|
| | file | rows | what it is | |
| |---|---:|---| |
| | `episodes.csv` | 1440 | one row per played negotiation: outcome, welfare, Gini, IR violations, rounds used, and per-episode belief scalars | |
| | `belief_turns.csv.gz` | 81672 | **the novel instrumentation** — one row per (episode, believer seat, turn): `posterior_mass_true_type`, `expected_utility_rmse`, `accept_set_f1` | |
| | `cells.csv` | 12 | per-cell aggregates with instance-clustered 95% intervals | |
| | `episodes/<cell_id>.jsonl.gz` | 12 files | complete episode records — every turn, parsed action, and belief block | |
| | `bank/` | 24 | the frozen instance bank, without which surplus columns cannot be recomputed | |
|
|
| Key columns: `experiment_name` (append-safe grouping), `cell_id`, `arm`, `deadline_rounds`, `host`, |
| `instance_id`, `seed`, `deal_rate`, `normalized_primary` (realized normalized utilitarian welfare over the |
| instance's feasible ceiling; a no-deal scores 0), `rounds_to_agreement`, `belief_auc_accept_set_f1`. |
|
|
| ### Reproducing the headline belief-accuracy numbers |
|
|
| The belief-F1 figures quoted in research note 0061 (0.210 / 0.228 / 0.241 / 0.244 / 0.241 across r4-r64) are |
| **`cells.csv.belief_auc_accept_set_f1`** — a per-episode time-average, then aggregated across episodes. |
| Taking a flat mean of the `accept_set_f1` column in `belief_turns.csv.gz` instead gives |
| 0.207 / 0.225 / 0.239 / 0.243 / 0.240, about 0.003 lower at every deadline, because that weights turns |
| equally rather than episodes and so over-weights long episodes. Both are defensible summaries of the same |
| data and the saturation conclusion is identical under either; use `cells.csv` to match the published table. |
|
|
| ## Experiment-name mapping |
|
|
| | experiment_name | description | |
| |---|---| |
| | `pure-rounds-sweep-v1` | the 12 complete cells below — `all_oracle` at [4, 8, 16, 32, 64, 128, 256], `all_rational` at [4, 8, 16, 32, 64] — at 120 episodes each (24 frozen parameter sets × seeds 0–4), unanimity, private information. The grid is deliberately incomplete: `all_rational` at 128 and 256 rounds is a stated gap (see Provenance). | |
|
|
| | cell | arm | deadline | episodes | host | deal rate | score | |
| |---|---|---:|---:|---|---:|---:| |
| | `all_oracle_r4` | all_oracle | 4 | 120 | tiger7 | 1.000 | 0.888 | |
| | `all_oracle_r8` | all_oracle | 8 | 120 | tiger7 | 1.000 | 0.884 | |
| | `all_oracle_r16` | all_oracle | 16 | 120 | tiger7 | 1.000 | 0.877 | |
| | `all_oracle_r32` | all_oracle | 32 | 120 | tiger7 | 1.000 | 0.899 | |
| | `all_oracle_r64` | all_oracle | 64 | 120 | tiger7 | 1.000 | 0.890 | |
| | `all_oracle_r128` | all_oracle | 128 | 120 | tiger7 | 1.000 | 0.884 | |
| | `all_oracle_r256` | all_oracle | 256 | 120 | tiger7 | 1.000 | 0.877 | |
| | `all_rational_r4` | all_rational | 4 | 120 | jagupard29 | 0.233 | 0.195 | |
| | `all_rational_r8` | all_rational | 8 | 120 | viscam1 | 0.267 | 0.230 | |
| | `all_rational_r16` | all_rational | 16 | 120 | jagupard34 | 0.208 | 0.182 | |
| | `all_rational_r32` | all_rational | 32 | 120 | jagupard34 | 0.208 | 0.178 | |
| | `all_rational_r64` | all_rational | 64 | 120 | iliad1 | 0.250 | 0.207 | |
|
|
| ## Two caveats that change how these numbers read |
|
|
| 1. **`all_oracle` is a flat control for AGGREGATES ONLY.** Closure and mean score are horizon-invariant, but |
| per episode — same host, same instance and seed — it lands on materially different deals at different |
| deadlines (91–97 of 120 differ, median |Δscore| 0.14). Do not run a paired within-episode oracle contrast |
| across deadlines. Its small residual aggregate variation is periodic in `(deadline + 1) mod 5`, the |
| identity of the rotating seat that holds the forced final. |
| 2. **Episode-level identity is host-dependent.** Around 3–6% of episodes in the `all_rational` arm sit on |
| near-ties whose resolution depends on the host CPU's float-summation order, usually flipping a whole |
| deal/no-deal outcome. The `host` column is provided for that reason; aggregate comparisons are unaffected |
| (the `rounds=4` cells are statistically indistinguishable from the frozen campaign), but episode-level |
| pairing across cells on different hosts is not clean. The `all_oracle` arm is unaffected. |
| |
| ## Regenerating this |
| |
| ```bash |
| # create the grid sweep, fan it out across Slurm CPU nodes, then close any preemption holes |
| uv run python experiments/rational_agents/launch_rounds_sweep.py --create-only |
| experiments/rational_agents/submit_rounds_sweep.sh --sweep-id <entity>/<project>/<id> --jobs 5 --cpus 16 \ |
| -- --shards-per-cell 16 --shard-timeout-s 10800 --bootstrap-samples 2000 |
| uv run python experiments/rational_agents/launch_rounds_sweep.py --sweep-id <id> --fill-missing |
| # then package and upload |
| uv run python experiments/rational_agents/package_hf_rounds_sweep.py --out /tmp/rounds_sweep_hf |
| uv run python experiments/rational_agents/upload_hf_publication.py --folder /tmp/rounds_sweep_hf --repo siddharthmb/2026.RA.Pure-Rounds-Sweep |
| ``` |
| |
| ## Provenance |
| |
| - **W&B sweep:** https://wandb.ai/siddharth-stanford/rational_agents/sweeps/ufrdew0j (a real `method: grid` sweep over arm × rounds; one run per cell) |
| - **Cluster artifacts:** `/nlp/scr/siddharth/ii_mats/rational_agents/pure_rounds_sweep_v1/` — per-cell run |
| directories in the ordinary schema, per-cell records under `control/cells/`, manifest at |
| `control/campaign_manifest.json` (status `partial-final-12`) |
| - **Slurm logs:** `/juice2/u/siddharth/ii_mats/logs/rounds_sweep/<jobid>.out`, first line of each is the exact |
| invocation |
| - **Bank:** `experiments/rational_agents/instances_five_seat_private_v2`, manifest SHA-256 |
| `cd32ebdef8072da3…` |
| - **Known gap:** `all_rational_r128` and `all_rational_r256` are absent — r256 lost every shard to a cluster |
| preemption and r128 was still refilling at publication time. They will be appended under the same |
| `experiment_name` when they land. |
|
|
| ## Related |
|
|
| - `siddharthmb/2026.RA.Quorum-Rounds-Sweep` — the agreement-rule axis: relaxing unanimity *does* move closure |
| (0.217 → 0.908), which is the contrast that makes this null informative |
| - `siddharthmb/2026.RA.Agent-Variants-Closure` — the preference-sharing axis, the other lever that works |
| - `siddharthmb/2026.RA.Five-Seat-Frontier-Negotiation` — the frozen campaign these cells are anchored against |
|
|
