mayatnikovandClaude Opus 4.7
08ac2e1bc1
Operator reported the bot wandered the same 50×50 patch for 2 hours
without making any progress toward food. Diagnosis showed three root
causes; this commit addresses all five open improvement_requests
the LLM (postmortem + tuner) flagged automatically.
Research basis (`Voyager`, `Plan4MC`, `GITM`, `Mindcraft`):
- Coverage / commit-to-cardinal exploration when local scan fails
- Biome-aware strategy switching using a static affordance table
- Wedge detector above the skill layer that triggers RELOCATE not
RETRY (per-skill stuck checks reset on re-entry — useless)
- Time-in-region bbox heuristic + need-duration AND skill-cycle gate
Concrete changes:
1. `runtime/goal/storyline.js`
- orient_self.completed: added timeout fallback (HP=full + session
>120s → done) so barren biomes don't block the bot on step 1.
Closes improvement #2 'Нет навыка оценки когда сменить район'.
- first_food.suggestSkill: now picks survive.scout-food (new) when
no passive mob is nearby; falls back to survive.acquire-food only
when something is in immediate range.
2. `runtime/biome-affordances.js` (new)
- Static table: 40+ biomes → {has_passive_mobs, has_trees,
has_water, has_crops, livable}.
- Unknown biomes return optimistic defaults to avoid regressions.
- Closes improvement #1 'Нет навыка целевого поиска еды по биому'.
3. `runtime/skills/scout-food.js` (new — survive.scout-food)
- Tiered strategy: biome check → scan 32 → scan 64 → commit a
cardinal for 200 blocks rescanning every 16. On cardinal
exhaustion, returns code:"exhausted" so the curriculum can
escalate to village.relocate.
- In barren biomes (desert/ocean/snowy_plains) the scan is
SKIPPED — bot walks straight toward the nearest neighbour
biome that affords passive mobs (8-direction biome probe at
radius 64).
4. `runtime/awareness/wedge-detector.js` (new)
- Rolling 10-min position bbox tracker. observe() called every
tick; isWedged() returns true when bbox<50 AND active need
unmet >5min AND skill cycles ≥3.
- markRelocationStarted() suppresses further wedge firings
until the bot has displaced ≥200b — prevents stack overflow
of relocate calls.
- Lives ABOVE the skill layer (in runtime/reflex.js), because
any per-skill stuck check resets on re-entry.
5. `runtime/skills/relocate.js` (new — village.relocate)
- 300-block walk in least-recently-used cardinal (per-incident
memory in ctx.recentRelocations).
- Re-paths every 32 blocks, soft-tolerates pathfinder failures
(3 consecutive throws → exit with code:"stuck_in_place").
- Closes improvement #2 + #4 ('low success rate trigger').
6. `runtime/skills/escape-pit-safe.js` (new — recovery.escape-pit-safe)
- Surveys 4 cardinals AND ceiling height before committing.
Picks the direction with most open blocks (≥3, no lava).
Falls through to pillar-up only if ceiling clear ≥4b. Returns
code:"no_strategy" if both blocked so curriculum can escalate
to relocate.
- Closes improvement #3 'Нет навыка для безопасного выхода'.
7. `runtime/reflex.js`
- Wedge detector wired before manifesto/storyline. If wedge.wedged
is true, dispatches village.relocate directly and returns —
bypasses every other branch.
- ctx.disableWedge flag for tests.
8. `runtime/coach/advisor-trigger.js`
- LLM provider outage backoff: 3 consecutive http_400 / timeout /
network_error → suppress advisor for 10 min. Today's TimeWeb
gpt-5.4-mini was 400'ing for an hour straight; we were spending
trigger budget on dead calls. Closes improvement implicit gap
in #5.
9. `runtime/bot.js`
- Tracks botSpawnedAt; snapshot._sessionMs exposed for storyline
orient_self timeout fallback.
Tests: 396 green (was 378, +18):
- runtime/biome-affordances.test.js — 8 tests
- runtime/awareness/wedge-detector.test.js — 9 tests
- runtime/goal/storyline.test.js — 1 new test (orient_self timeout)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
67 lines
2.2 KiB
JavaScript
67 lines
2.2 KiB
JavaScript
import { test } from "node:test";
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import assert from "node:assert/strict";
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import {
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affordancesFor,
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hasPassiveMobs,
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hasTrees,
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hasWater,
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isLivable,
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isBarren,
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isUnlivable,
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__testing,
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} from "./biome-affordances.js";
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test("plains: full affordances (mobs + scattered trees)", () => {
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const a = affordancesFor("plains");
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assert.equal(a.has_passive_mobs, true);
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assert.equal(a.has_trees, true);
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assert.equal(a.livable, true);
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});
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test("desert: barren (no mobs, no trees, no water)", () => {
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assert.equal(hasPassiveMobs("desert"), false);
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assert.equal(hasTrees("desert"), false);
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assert.equal(hasWater("desert"), false);
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assert.equal(isBarren("desert"), true);
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assert.equal(isLivable("desert"), true, "desert is walkable, just empty");
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});
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test("ocean / deep_ocean: unlivable + has water", () => {
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assert.equal(isUnlivable("ocean"), true);
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assert.equal(isUnlivable("deep_ocean"), true);
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assert.equal(hasWater("ocean"), true);
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assert.equal(hasPassiveMobs("ocean"), false);
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});
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test("mushroom_fields: passive mobs (mooshroom) even though no other animals", () => {
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assert.equal(hasPassiveMobs("mushroom_fields"), true);
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assert.equal(isBarren("mushroom_fields"), false);
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});
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test("forest variants: trees + mobs", () => {
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for (const b of ["forest", "birch_forest", "dark_forest", "taiga", "snowy_taiga", "jungle", "swamp"]) {
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assert.equal(hasTrees(b), true, `${b} should have trees`);
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assert.equal(hasPassiveMobs(b), true, `${b} should have passive mobs`);
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}
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});
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test("badlands variants: no mobs, no trees (except wooded_badlands)", () => {
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assert.equal(hasPassiveMobs("badlands"), false);
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assert.equal(hasTrees("badlands"), false);
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assert.equal(hasTrees("wooded_badlands"), true, "wooded variant has trees");
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assert.equal(isBarren("badlands"), true);
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});
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test("unknown biome: optimistic defaults (don't cripple skills)", () => {
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const a = affordancesFor("not_a_real_biome_2026");
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assert.equal(a.has_passive_mobs, true);
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assert.equal(a.livable, true);
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});
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test("null / undefined: optimistic defaults", () => {
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assert.deepEqual(affordancesFor(null), __testing.DEFAULT);
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assert.deepEqual(affordancesFor(undefined), __testing.DEFAULT);
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assert.deepEqual(affordancesFor(42), __testing.DEFAULT);
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});
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