Measured, not assumed. With the gate temporarily opened to 20 deg, every
real shot was logged (tick, angle error at fire time, distance, power,
hit) across 3 gauntlets: 2611 shots, 57.3% aggregate. Findings:
- The geometric cone atan(BotRadius/d) is directionally confirmed but a
WEAK lever: even at 0.0-0.1 deg error the hit rate at 400-600px is only
~53-57%, because PREDICTION error dominates alignment error.
- Real effect of tightening the gate: 57.9% -> 68.0% aggregate hit rate
(fixed 0.1 deg), not the 76.9% previously reported -- that was a
high-variance draw (per-rep 62.8/66.4/77.2%).
- The shipped range-aware gate (SafetyFactor 0.6) does NOT beat the fixed
2.0 deg gate on hit rate (55.8% vs 57.9%, ~1.5 sigma, inside noise). It
fires 22-28% more shots and therefore lands more total hits (~509 vs
~434 per rep). No per-adversary score delta exceeded the 300-point
run-to-run noise band, so no config is demonstrably better on score.
Shipped anyway because it is strictly more expressive (a fixed threshold is
the special case), tunable from one const, and physically motivated, but
the honest verdict is recorded in-code: the gate is not the bottleneck.
AimThresholdDeg is removed; shouldFire now takes distPx. Degenerate or NaN
distance falls back to the ceiling rather than dividing by zero.
Also adds a per-shot logger to ModularBot behind 'const ShotLog' so the
measurement above is reproducible, and 10 new guard checks (24 total, all
passing) covering monotonicity, clamping, formula, perfect alignment,
gross misalignment and degenerate distance.
Cross-checked against the server source: the gun fires BEFORE the turn is
applied, so the logged angle error is the true departure error, and
fireAssist auto-aim is off (unset by the Nim API and forced false by
setAdjustRadarForGunTurn).
Four guns cached a whole prediction per tick while predict() is called once
per power bin, so every bin after the first (and the real fired shot, which
shares lastState) reused the power-1.0 lead. Fixed by caching only the
speed-INDEPENDENT derived state and recomputing the lead per requested speed:
- stop_shot: also fixes prevSpeed being written before it was read, which
made abs(speed) < abs(prev) permanently false and the entire
stop-prediction branch unreachable (it was just Linear).
- displacement: the cache key included bulletSpeed, so the guard missed on
all four bins and the 15-tick window advanced ~4x/tick, making the
inferred velocity ~4x too small.
- averaged_lead: tick cache removed outright. pattern_matcher: split into
speed-independent match+path and per-call lead.
FeedbackEvent gains fireTick/powerBin (additive; only virtual_bullets
constructs one) so guns can pair feedback to the exact shot instead of
guessing by coordinates. tsetlin uses it: traces are now keyed exactly by
(fireTick, powerBin) with a 1024-slot ring, and the 10-frame window shifts
at most once per tick (it was shifting ~4-5x/tick, so isWarmedUp tripped
after ~2 ticks).
KNOWN INCOMPLETE: tsetlin still does not diverge from Linear in battle. The
two named bugs are fixed (a 600-tick sim shows trainedShots=2141,
traceMisses=0, and a fixed-input probe converges to a 9.6px correction), but
the TM's clause feedback itself is broken: ~131 of 1740 literals end up
included per clause, so its conjunction never fires. Sweeping TM_S,
TM_N_CLAUSES and a two-branch Type-I update did not change the correction
from 0. Needs a real TM fix or removal, not another bug fix.
First-ever guard tests for the gun selector: common_libs/tests/
test_gun_harness.nim (14 checks, headless, no Java). There were none before,
which is how six broken guns survived a full analysis cycle. Against the
previous HEAD, 5 of these checks FAIL - that is the regression guard.
Wave queues (guess_factor, decay_gf, knn_gun): predict() stored ONE wave
per tick while onResult() popped one per resolved bullet (~4/tick), so the
queue drained to empty within a few dozen ticks, ~3 of every 4 resolutions
returned without learning, and the survivor paired with a same-tick wave
(bearingDelta ~= 0) pinning the histogram at centre. PROOF: GF.vHits ==
HeadOn.vHits and DecayGF.vHits == HeadOn.vHits byte-for-byte in every one
of 50 rounds — the guns had degenerated to HeadOn.
Now each gun keeps a per-bin FIFO with an O(1) head cursor. At most one
push per (tick, bin) so the fire site's 5th predict() call is a no-op, and
onResult pops the oldest wave of its OWN bin via e.bulletPower. Aiming
math untouched (it was already correct: 0 deg = East, CCW+).
maxBullets 2048 -> 8192: the rack spawns 52 bullets/tick so the ring wrapped
every ~39 ticks while a long power-3 shot needs ~90, silently discarding
unresolved bullets and biasing every measured hit rate by range. Added a
droppedBullets counter so a future overflow is measurable, and wavePushes/
waveStarved counters on the three guns. After the fix: vDropped = 0 and
vStarved = 0 across all 48 recorded rounds.
fitnessFor is now exported, deterministic (enemies iterated in ascending id
order) and shared by the selector and the stats dump, replacing a hand-rolled
merge in ModularBot that never advanced its window head.
Round lines gain additive keys: vDropped, vStarved.
Attribution is proven, not guessed: the server assigns a per-round-unique
bulletId (GunEngine.nextBulletId) and stamps the same id on BulletFired,
BulletHitBot, BulletHitWall and BulletHitBullet. Keep a FIFO of fired gun
ids, stamp bulletId -> gunId on onBulletFired, resolve through that map.
Hits are deferred when onBulletHit precedes onBulletFired in the same
turn (client dispatches priority 70 > 60), which recovered 14
unattributed hits. 99.9% of shots and 99.8% of hits attributed.
Stats lines now carry per-gun realShots/realHits/realHitRate; the old
keys and round-level totals are unchanged.
bestPower: a gun with zero observations in every bin previously returned
the HIGHEST bin (power 3.0) because an empty bin satisfied the
'count == 0' clause on the first countdown iteration. Cold guns now
return the lowest bin as the docstring always claimed. Warm-gun path
untouched.
- bestGun: replace first-index-wins argmax with random pick among guns
within TieMargin (2%) of best rate. HeadOn at index 0 was silently
winning every tie, starving Tsetlin/Linear/etc.
- MinObsBeforeCompete 15 -> 50 (Pattern entered competition on noise)
- add MinHitRateFloor 0.10: if no gun clears it, fall back to HeadOn
instead of selecting the best of a bad field
- ModularBot: remove AntiSurfer gun (0% virtual hit rate everywhere),
14 -> 13 guns, renumber ids and selection counters
- 30-tick cooldown after ghost-stuck/timeout ram exit prevents re-entry loop
- enemy_tracker.update() skips dead bots to prevent same-tick scan resurrection
- TFIL graphics cleared when ramming is active movement
- [config] logs: white base with green-highlighted changes only
- [ram:enter] logs trigger reason and key values on false→true transition
- [death] and [target-invalid] logs retained for diagnostics
PhantomMeteor:
- Ram finisher: charge at enemy when <200px and their energy <10
- Ram opportunity: charge when <60px and we have >20 energy advantage
- Integrated gunheat tracker for 1-2 tick earlier wave detection
- Distance control: smooth linear ramp toward preferred engagement distance
- Phantom range expanded 150→250px to catch closer threats
WaveSurfer:
- Wall-aware dodge bin selection: penalize bins leading off-arena
- Dodge timing: predict future position 15 ticks ahead for safety
- Distance control: radial blend when outside deadband (350±50px)
- Wall escape: invert strafe if pushing further into wall, blend toward center
ModularBot:
- Wired KNN gun (purple/magenta)
- Shadows tracked for movement (safer GF prediction)
- Bullet lifecycle management (onBulletFired/onBulletHitBot/onBulletHitWall)
- Unified phantom_meteor movement (wave_surfer unplugged)
- Config logging on round start + gun switch
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Gun selector now gates competition: guns with <15 total observations across
all power bins sit out until at least one gun qualifies. Falls back to ungated
selection if no gun reaches threshold, preventing cold-start stalls.
Sliding window increased from 50 to 100 ticks to reduce switching noise.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
New DrussGT-inspired modules:
- KNNGun: K-nearest-neighbor statistical targeting using GF density peaks
- GunheatTracker: dual-heat system (predicted + confirmed) for 1-2 tick lead
- ShadowTracker: computes GF regions safe from in-flight bullets (enemy wave dodge)
VirtualBodyTracker now integrates gunheat for earlier fire detection and shadows
for safe-zone multiplier (90% reduction in danger zones).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Renames PatternMover_garage → PatternMover, RandomMover_garage → RandomMover,
WaveSurfer_garage → WaveSurfer. Updates all .json, .sh, .nimble, and config.nims
files to match TR Booter naming convention (directory name = bot name).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements VirtualBodyTracker (wave-based hit/miss scoring) instead of EMA damage accumulation. Movement switching now happens every tick, not every 3 rounds. Also refactors radar colors to dark teal (#004444/#0D4D4D) for faint visibility.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Cold-start bug: uniform bins[0..30]=0.1 made peakBin() always return
0 (first-wins tie), giving GF=-1 (max CW escape) before any learning.
Fixed with a triangular head-on bump at bin 15 (GF=0) as the prior.
- onResult now recomputes mea from FeedbackEvent.bulletPower instead of
the stale first-bin mea cached by predict; correct per-power-bin GF.
- Add DebugGF const (default false) with [gf-dbg] echoes in predict/onResult.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Two bugs fixed:
1. Multi-tick gaps: turn rate assumed 1 tick between observations, but scans can be 5+ ticks apart. Now divides by actual tickDelta.
2. Per-power-bin state corruption: predict() called 4x per tick (per power bin). After first call, prevHeading was already updated, causing subsequent calls to compute 0° delta. Now captures oldHeading/oldTick before updating.
Verified: OscillatorBot at 4°/tick captured correctly; normalization [-180°,180°] works; tickDelta=1 typical; first bin gets delta, subsequent bins see 0 (expected).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add maxSpeed param (default true) to runBattleRunner/runBattle
- Drain stdout in poll loop — Java blocked on full pipe buffer causing timeout
- TestBattleRunner.java already had --max-speed; .class was stale and needed recompile
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds TR_SAMPLE_BOTS env var support to point to external sample bots (Walls, Fire, SpinBot, etc). Updates test_bullet_economy.nim to use Walls from the sample-bots directory instead of custom WallsBot, removing the hardcoded path dependency.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Document exception handling, zero-value BotResult trap, shared adversary bots
- Add offline parsing example using parseServerOutput
- Skip tests gracefully when JARs missing (guard before suite blocks)
- Fix blocking readLine in runner_process.nim: poll with 50ms sleep + atEnd check
(was preventing timeout enforcement, now blocks correctly during battle)
- Add test task to QBot.nimble and config.nims setup docs to AGENTS.md
- Add debug logging to TestBattleRunner for bot identity tracking
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements:
- BattleResult type and JSON-lines parser (#127)
- TR server lifecycle manager (#128)
- Bot compiler using nim c (#129)
- runBattle() orchestrator (#130)
- Example test in OscillatorBot_garage (#131)
- Framework usage guide (#132)
- TestBattleRunner.java for external server (#133)
- BattleRunner process lifecycle (#134)
Fix: runner_process.nim was redefining TimeoutError locally; now
uses std/net.TimeoutError consistently with server_manager.nim.
- Deleted constants.nim, event_queue.nim, graphics.nim, json_parse.nim, schemas.nim, utils.nim, and ws_client.nim files.
- This cleanup removes unused code and simplifies the codebase, focusing on essential functionalities.
SirStone