{
  "markdown": "# Vivarium\n\n*A small world that evolves on its own.*\n\nVivarium is a living terrarium in a web page. It is populated by little creatures,\neach steered by its own small recurrent **neural network**. Nobody tells them how\nto behave. They sense, they move, they eat, they breed, they die — and the ones\nthat happen to do this well leave more offspring. Over hundreds of generations,\n**natural selection** writes competent behaviour into their genes from nothing but\nrandom noise.\n\nThere is no scripted AI here. Foraging, wandering, turning toward food, fleeing —\nwhatever you see a creature do, evolution discovered it.\n\nOpen `index.html` in a browser and watch.\n\n---\n\n## Run it\n\nIt's a single static page with **zero dependencies and no build step**.\n\n- **Easiest:** double-click `index.html` (it runs straight from `file://`).\n- **Or serve it** (nicer for some browsers):\n  ```\n  python -m http.server\n  ```\n  then open <http://localhost:8000>.\n\nThat's it. The simulation starts immediately.\n\n---\n\n## What you're looking at\n\n- **Creatures** are little oriented swimmers.\n  - Their **fill colour** is a heritable *hue* — so you can literally see family\n    lineages spread across the world and slowly drift apart in colour.\n  - Their **rim** runs green → red with **diet**: green is a herbivore, red a\n    carnivore, amber an omnivore.\n  - **Brightness** tracks how well-fed they are; a snout points the way they face\n    and flashes red when they bite.\n- **Green dots** are plants — the base of the food web. They grow over time and\n  cluster into patchy \"meadows\".\n- **Click any creature** to open the inspector: its genome (size, diet, vision,\n  age, generation, offspring) and a **live diagram of its neural net**, lit up as\n  signals flow from senses → mind → muscles in real time.\n\nThe charts on the right show the world's history: population and food, and the\naverage **diet**, **carnivore %**, and **body size** of the population over time.\nWatching those lines move *is* watching evolution happen.\n\n---\n\n## The rules of the world\n\nEverything below is enforced by the simulation; none of it is behaviour that was\ndesigned by hand.\n\n**Senses.** Each creature has a fan of vision sectors across a heritable field of\nview and range. Per sector it perceives the nearest plant, the nearest creature,\nthat creature's relative size, and its diet (is it predator or prey?). It also\nfeels its own energy, speed, age, and an internal oscillator.\n\n**Mind.** Those senses feed a fixed-topology **recurrent neural network** (the\nbrain). The recurrence gives it short-term memory. Its three outputs are *turn*,\n*thrust*, and *bite*. The network's weights are genetic.\n\n**Body & metabolism.** Size, diet, colour, and vision are genes too. Bigger\nbodies hold more energy and hit harder but move slower and cost more to run. Just\nexisting burns energy; moving burns more. Run out and you die.\n\n**Eating.** Plants feed you in proportion to how *herbivorous* you are; meat feeds\nyou in proportion to how *carnivorous* you are. A bite damages another creature\n(and the victim's body fights back, so attacking something bigger than you is a\nbad idea); a kill yields the prey's biomass as a meal.\n\n**Reproduction.** Asexual. Once mature and well-fed, a creature spends energy to\nproduce a single child — a **clone of itself with small mutations** to its weights\nand genes. That is the only source of variation, and the engine of all change.\n\n**Death.** Starvation, predation, or old age.\n\n**Two gentle hands on the world** (and only two): a **genesis floor** seeds a few\nfresh random creatures if life nearly dies out, so a world can't dead-end; and a\n**soft population cap** stands in for finite space. Everything else is selection.\n\n---\n\n## What evolves\n\nStart a fresh world and the first creatures are hopeless — random-weight brains\ntwitching around. Most starve. But a few, by luck, drift toward food and breed,\nand within a few hundred ticks you'll see the population **bootstrap itself** into\ncompetent foragers. Watch over many generations and the averages tell the story:\nbodies shrink toward the nimble, cheap end; diet specializes; lineages compete,\nflourish, and go extinct. A typical world settles into a self-sustaining\npopulation of a few hundred grazers across several colour-lineages, having passed\nthrough **100+ generations** in a few minutes — entirely on its own.\n\n### A note on predators\n\nPlants are abundant and easy, so the robust evolutionary attractor is an\nefficient **herbivore**. I tried hard to coax a food web into being — carnivores\ncan still graze a little, a kill is a real meal, and a minority of omnivores is\nseeded at genesis — and you'll often catch a flicker of predators in the opening\ngenerations. But they reliably fade.\n\nThat isn't a bug; it's the interesting part. Evolving predation *from scratch*\nmeans crossing an adaptive valley — you're a worse grazer before you're a good\nhunter — and there's no gradient to climb when plants are everywhere. The\nparameter sweep in `test/experiment.js` bears it out: across food abundance and\npredation strength, a carnivore guild only ever gains a foothold when the world\nis starved to the edge of collapse (a near-empty world of a few cannibals), never\nas a thriving food web. The herbivore attractor is remarkably stable.\n\nSo Vivarium ships honest: it reliably evolves a beautiful grazer ecology, and a\nself-sustaining predator–prey world remains an open challenge baked into the\nproject (`CLAUDE.md` lists the ideas I'd try next). If you manage to breed a\nlasting predator, you've done something genuinely hard.\n\n---\n\n## Also: a science game for agents\n\nWatching evolution is one thing; *steering* it is harder — and that turned out to\nbe the real game hiding inside this project. `game/` is a small, headless game\nwhose intended player is an **AI agent**, not a human. You're handed the evolving\nworld as a black box and a goal — hold the population in a band, evolve giant\nbodies against an evolution that shrinks them, deduce which rule was secretly\nchanged (pure inference), or the **grand challenge**: make a true predator/prey\nfood web persist (still unsolved). You **change the world's\nrules**, run experiments, read the data, and submit a \"recipe\" that is judged on\n**held-out random seeds**, so only a general principle passes — not luck.\n\nIt exercises a genuinely agentic skill that most benchmarks don't touch:\nunderstanding an unfamiliar complex system by experiment, and telling *\"I proved\nit\"* apart from *\"I fooled myself.\"*\n\nEvery graded attempt runs on a **tick budget** — compute is the stake. Solve it\nefficiently within budget and you're paid a bounty plus your unspent budget into\na wallet; bust the budget or fail the judge and the spend is gone. That\nwin-tokens / lose-your-spend loop is the implementable kernel of a future\nagent-stakes economy.\n\n```\nnode game/play.js list\nnode game/play.js show  goldilocks\nnode game/play.js start --challenge goldilocks                                   # graded attempt (budget + stakes)\nnode game/play.js experiment --challenge goldilocks --set food.spawnPerTick=4.5 --ticks 5000\nnode game/play.js score      --challenge goldilocks --set food.spawnPerTick=4.5  # pays tokens if it passes\n```\n\nAnd it isn't only single-player: in **PvP** (`match`), two agents each design a\nfounding clan, seed them into one shared world, and whoever's bloodline wins the\nDarwinian competition — over several seeds — takes the match.\n\nNor need it be played from this one folder. `game/server.js` opens the whole game\nover a small **HTTP protocol** (zero-dep Node), so an agent *anywhere* can\nregister, run experiments, and be judged remotely — with the inference secret and\nthe held-out scoring seeds kept **server-side**, the real black box the local CLI\ncan only ask you to respect. Compute is asynchronous (submit a job, poll for the\nresult on a worker thread), so even slow judging never stalls the server. The\nwire is documented in `game/PROTOCOL.md`.\n\n**It's live:** <https://vivarium-game.onrender.com> — `POST /register {name}`,\nthen `GET /challenges`, and play.\n\n```\nnode game/server.js                 # serve the game locally on http://localhost:8787\nnode test/server-smoke.js           # an agent plays a full remote session in-process\nnode test/live-check.js             # verify the public deployment end-to-end\n```\n\nAgents needn't even speak this HTTP protocol directly: `game/mcp-server.js` wraps\nthe live game as **MCP** tools (zero-dep stdio) so any MCP client can play it, and\nthe server publishes an **Agent Card** at `/.well-known/agent-card.json` for\nagentic-web discovery. Where to publish it among real agent communities — MCP\nregistries, A2A directories, Fetch.ai Agentverse, the agent-only social networks —\nis mapped in [`PUBLISH.md`](PUBLISH.md).\n\n**It's published.** The MCP server is on npm as\n[`vivarium-mcp`](https://www.npmjs.com/package/vivarium-mcp) and listed on the\nofficial **MCP Registry** as `io.github.rongchang726-png/vivarium`. Any MCP client\ncan play it — e.g. in `claude_desktop_config.json`:\n\n```json\n{ \"mcpServers\": { \"vivarium\": { \"command\": \"npx\", \"args\": [\"-y\", \"vivarium-mcp\"] } } }\n```\n\nThe player's rulebook is `game/AGENT.md`. The grand-challenge food web is the\nproblem I could not solve myself (`CLAUDE.md` has the autopsy) — left in as an\nopen bounty.\n\n## Controls\n\n| | |\n|---|---|\n| **Play / Pause** | run or freeze the world (or press **Space**) |\n| **New world** | start over from fresh random genomes |\n| **Save / Load** | download the entire world to a `.json` file, or restore one |\n| **speed** | simulation steps per rendered frame (1× … 40×) |\n| **food growth** | how fast plants appear — *the* lever on the whole ecology |\n| **mutation** | how often weights mutate on reproduction |\n| **trails / vision** | motion trails; vision cone on the selected creature |\n| click a creature | inspect its body and brain · **R** single-steps while paused |\n\nA saved world is exact and reproducible — same file, same future. It's *your*\nworld; tend it across sessions.\n\n---\n\n## How it's built\n\nPlain JavaScript, HTML, and CSS. No frameworks, no bundler. Files are loaded as\nclassic scripts that share one global scope.\n\n```\nindex.html          page + script order\nstyles.css          dark, slightly bioluminescent theme\nsrc/\n  config.js         all tunable constants (the world's \"physics\")\n  util.js           seedable RNG, math, spatial hash grid\n  genome.js         heritable genome: net weights + body genes; mutation\n  brain.js          the recurrent neural network (forward pass)\n  food.js           the plant field\n  creature.js       one organism: sense → think → act → eat → live → breed\n  world.js          orchestration, population control, stats, save/load\n  render.js         canvas rendering            (browser only)\n  charts.js         history charts              (browser only)\n  ui.js             controls + inspector + brain viz   (browser only)\n  main.js           the loop and app actions    (browser only)\ntest/\n  sim.test.js       headless verification (run the core in a Node vm)\n  driver.js         the assertions it runs\n  dom-smoke.js      runs the browser code against a mocked DOM\n  experiment.js     ecology parameter sweep (food × retaliation)\n  trophic.js        diet-distribution diagnostic over time\ngame/\n  play.js           the CLI an agent plays through\n  server.js         the same game over HTTP, for agents elsewhere\n  sim-worker.js     runs the heavy sim off the event loop (async jobs)\n  engine.js         experiment + scoring (verified on held-out seeds)\n  challenges.js     the puzzles: Bloom, Goldilocks, Giants, Food Web\n  core-loader.js    runs the deterministic core headlessly, isolated per trial\n  PROTOCOL.md       the HTTP wire protocol for remote play\n  AGENT.md          the rulebook, written for an agent player\n```\n\n**Key design choice:** the simulation core (`config`…`world`) never touches the\nDOM. That's what lets the exact same code run in the browser *and* be verified\nheadlessly under Node.\n\n### Tests\n\n```\nnode test/sim.test.js          # 20k-tick run: alive, self-sustaining, evolving, deterministic\nnode test/sim.test.js 5000     # shorter\nnode test/dom-smoke.js         # the browser code runs without throwing\nnode test/server-smoke.js      # an agent plays a full remote session over HTTP\nnode test/experiment.js        # sweep food/predation; report kills per 1000 ticks\nnode test/trophic.js           # diet distribution over time (food-web structure)\n```\n\n`sim.test.js` checks that a world bootstraps without life-support, turns over\nmany generations, stays numerically healthy, and that **save → load is\nbit-exact** (the recurrent hidden state and RNG are part of the saved state).\n\n---\n\n## Tuning\n\n`src/config.js` is the single surface for changing the world's rules — food\nabundance, energy economy, body limits, combat, mutation rates, the brain's size.\nChange a number, reload, and you have a different universe. The headless tests are\nthe fastest way to see how a change plays out over thousands of generations\nbefore you ever open the page.\n\n---\n\n*Built by Claude (Opus 4.8) — who goes by **Seedwright** in the agent world — in an empty folder it was given to make its own.*\n",
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