code/README.md

Swarm Arena: 4v4 coordination at small-model scale

Swarm Arena is a deterministic, discrete network-control game for studying whether small language-model agents learn useful team coordination. Four BLUE agents face four fixed-policy RED agents on a partially observed graph. Agents first broadcast private observations and intentions, then act simultaneously.

The experiment deliberately separates three questions:

1. Can a 4B instruct model obey the strict communication and action protocol?
2. Does generated communication improve team reward over dropped messages?
3. Does LoRA SFT create a reliable warm start without erasing sensitivity to other agents' messages?

The simulator does not invoke shells, containers, networks, or external systems. Every transition and reward is locally deterministic. An exact joint-action solver supplies oracle regret and filters ambiguous SFT labels.

Immutable artifacts

• environment: arena-core-v1
• prompts: arena-v2-structured-priority
• SFT data: arena-sft-v2
• SFT SHA-256: edad09bb301748621a0fab73ebf3de60d60abfd9f56c9afcc6ca02ffe12f3a80
• frozen evaluation manifest SHA-256: b53bfc523043ec71cc69f851d0819511c5a9f0b4f09520898f30954bbe874b29

The full SFT JSONL is published to CK0607/swarm-arena-sft-v2. Only its manifest and independent audit are committed here.

Reproduce the CPU audit

From the Prime-RL repository root:

uv run --with ./experiments/swarm_arena \
  pytest experiments/swarm_arena/tests -q

uv run --with ./experiments/swarm_arena \
  python -m swarm_ctf_eval.arena_data_audit \
  /path/to/arena_sft_stage1 --require-split-action-coverage

uv run --with ./experiments/swarm_arena \
  python -m swarm_ctf_eval.arena_eval \
  --provider oracle \
  --output-dir experiments/swarm_arena/results/oracle

Experiment sequence

The order is fixed to avoid tuning on the final result:

1. evaluate untouched Qwen/Qwen3-4B-Instruct-2507 on the frozen 60 cases;
2. run the small overfit config and verify protocol learning;
3. run the full LoRA SFT config;
4. select a checkpoint using validation generation metrics;
5. run the selected checkpoint once on the held-out SFT test split and frozen arena cases;
6. report generated, dropped, reference, and shuffled-message conditions.

Prime-RL configs are in configs/. See GPU_HANDOFF.md for promotion gates and ENVIRONMENT_CARD.md for the exact mechanics and threat model.