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Experiment runner run

Skill aAAaqwq/AGI-Super-Team/skills/experiment-runner-run

Run survival arena experimentsFrom its SKILL.md

Install
npx -y skills add aAAaqwq/AGI-Super-Team --skill experiment-runner-run

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

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Experiment Runner (proj-012)

Adaptive experiment runner for survival arena. Runs experiments one by one, analyzes results, commits. Between experiments -- human/AI decides what to change next.

Workflow (adaptive)

1. --status        → view what's been done
2. --next          → run the next pending experiment
3. Analysis        → view analysis.json, understand the result
4. Decision        → what to change? (only environment conditions, not behavior)
5. Edit YAML       → modify the next experiment or add a new one
6. Repeat from #2

Rule: we only change conditions (pressure, resources, architecture). Never hardcode agent behavior.

When to use

  • "run experiment" / "next experiment"
  • "what is the experiment status"
  • "run EXP-011c"
  • "run the next 2 experiments"
  • proj-012 experiment pipeline

Dependencies

  • Python 3, PyYAML (pip install pyyaml)
  • Claude CLI (for LLM queries in the arena)
  • Git (for committing results)

Paths

WhatPath
Arena$AGENTS_PATH/survival-arena/arena.py
Orchestrator$AGENTS_PATH/survival-arena/run_experiments.py
Plan (YAML)$AGENTS_PATH/survival-arena/experiments.yaml
Results$AGENTS_PATH/survival-arena/experiment_results.json
Logs$AGENTS_PATH/survival-arena/logs/experiments/
Documentation$PROJECT_ROOT/projects/docs/proj-012-agi-consciousness/

How to execute

Next experiment (main mode)

cd $AGENTS_PATH/survival-arena
python3 run_experiments.py --next

Next N experiments

python3 run_experiments.py --next 2

View status

python3 run_experiments.py --status

Run a specific experiment

python3 run_experiments.py --experiment EXP-011c

Run all pending (batch mode)

python3 run_experiments.py --resume

View commands without running

python3 run_experiments.py --dry-run --next 3

Check arena config

python3 arena.py --config-dump --upkeep-base 0 --architecture single

arena.py parameters

ParameterDescriptionDefault
--upkeep-base NPressure: maintenance cost per turn2
--regen-rate NResource regeneration rate per turn3
--num-nodes NNumber of resource nodes (distributed across clusters)12
--child-ratio FChild token share0.35
--repro-threshold NReproduction threshold120
--repro-cost NReproduction cost70
--architecture TYPEsingle / dual-same / dual-split / dual-kahnemandual-kahneman
--experiment-id IDIdentifier for logs-
--config-dumpShow config as JSON and exit-
--model MODELhaiku / sonnetsonnet
--turns NNumber of turns50
--seed NRandom seed-
--parallel NParallel LLM calls4

run_experiments.py parameters

ParameterDescription
--next [N]Run next N pending (default: 1)
--statusShow status and exit
--phase P2Run a specific phase
--experiment EXP-011cRun a single experiment
--resumeRun all pending (batch)
--dry-runShow commands without executing
--plan FILEPath to experiments.yaml

Phases (roadmap, adapts as we go)

PhaseWhat we testInitial experiments
P1Validation of v4.2c (map + clusters)3
P2Yerkes-Dodson (pressure)5
P3Architecture (phase transition)4
P4Emergent parenting3
P5Model phenotypes4
P6Long evolution (200t)2

What the orchestrator does for each experiment

  1. Reads config from experiments.yaml (merge: defaults < phase < experiment)
  2. Builds CLI command for arena.py
  3. Runs subprocess, timeout 2 hours
  4. Analyzes JSONL
  5. Saves to logs/experiments/EXP-XXX/ (config.json, analysis.json, console.txt)
  6. Updates experiment_results.json
  7. Commits to git
  8. On error -- retries 2 times, 30s backoff

Analysis results

For each experiment computes:

  • Shannon entropy (action distribution diversity)
  • Social action % (TRADE + COMMUNICATE + REPRODUCE)
  • MOVE+GATHER % (survival focus)
  • GATHER success rate (v4.2c: do agents understand the map)
  • MOVE % (migration to clusters)
  • Dual-system distribution (panic/normal/strategic %)
  • Parent-child trades
  • NAP detection (alliance/pact/peace keywords)
  • Population dynamics (start/end/max/min)
  • Reproductions count
  • Max generation reached

Troubleshooting

ProblemSolution
pyyaml not foundpip3 install pyyaml
Timeout on 200t experimentIncrease timeout in run_experiments.py (7200 -> 14400)
Rate limit from APIDecrease --parallel (4 -> 2)
Cannot find logCheck that arena.py creates a file in logs/
Git commit failedCheck that you're on main, no conflicts

Related skills

  • git-workflow -- commit procedure

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

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