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End of preview. Expand in Data Studio

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

# 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
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