| name | cogamer.evaluate |
| description | Run multi-episode CvC evaluation and produce structured JSON metrics |
Evaluate
Run multi-episode evaluation and produce structured metrics.
Announce at start: "I'm using the evaluate skill to run multi-episode scoring."
Command
softmax cogames eval -m <mission> -p class=cvc_policy.cogamer_policy.CvCPolicy -e <episodes> --format json
Defaults: mission=machina_1, episodes=10.
Reading Results
The JSON output contains per-episode rewards, assignments, and timeouts. Parse it to compute:
- Average reward per policy
- Win rate across episodes
- Timeout count (indicates policy is too slow)
Multi-Seed Evaluation
For robust comparison (e.g. before/after a code change), run multiple seeds:
for seed in 42 43 44 45 46; do
softmax cogames eval -m machina_1 -p class=cvc_policy.cogamer_policy.CvCPolicy -e 5 --seed $seed --format json
done
Comparing Policies
Evaluate two policies side by side:
softmax cogames eval -m machina_1 -p class=cvc_policy.cogamer_policy.CvCPolicy -p class=baseline -e 10 --format json
Customization
--mission <name> or -m (supports wildcards)
--episodes <n> or -e
--seed <n> for reproducibility
--steps <n> or -s to override max steps
--format json or --format yaml
After Evaluation
Use the metrics to establish baselines or confirm improvements. Feed results to /cogamer.analyze for diagnosis.