07866c99bd65a603322ec7c9be12e1b7db6f10d8
17 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 SirStone
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5e32ec16df |
j142 retire the ADE+SBC gun (rack id 17): the owner watched it, it does not learn, throw it away
Remove guns/bitbrain_net.nim (+README), test_bitbrain_net.nim,
measure_bitbrain_scaling.nim, rack id 17 and all of its plumbing in
selector.nim / ModularBot.nim / env_report.nim, the TR_BITBRAIN_NET switch
and the NEW-NETWORK TR_BITBRAIN_* knobs, and the BitBrainNet arm of
run_prediction_quality.nim.
With id 17 gone there is nothing to disambiguate, so the legacy namespace
becomes the ONLY one: TR_RACK_BITBRAIN always selects id 16 LEADGAIN and
every TR_BITBRAIN_<X> in the frozen 14-suffix alias set always means
TR_LEADGAIN_<X>. The alias layer and its [depr] line stay.
KEPT: the common_libs/bitbrain/ SBC library (learned_surfer imports
bitbrain/sbc), lead_gain at id 16 with env TR_LEADGAIN_* and log tag [lg],
and the
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SirStone
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c9b67530db |
j141 fix: the per-gun real-shot accounting was still array[17] after rack id 17 landed
REGRESSION: the live bot stopped firing entirely and moved degenerately whenever a rack admitted rack id 17 (the ADE+SBC BITBRAIN gun added in |
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SirStone
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59c5af0499 |
j140 fix: a pre-rename .env must not admit the disabled BitBrain net gun
TR_RACK_BITBRAIN=both is what the owner's live .env carries, and with the new ADE+SBC gun registered at id 17 under the SAME rack name that value was also landing on id 17 - so a gun that was not enabled (TR_BITBRAIN_NET unset) was admitted into the rack and its placeholder predictions were pushed into the shared VirtualTracker ring, which shifts every other gun's learning order. While the namespace is LEGACY, loadRackMembership now skips id 17's TR_RACK_BITBRAIN entirely, so that value addresses ONLY the gun it always addressed (LEADGAIN, id 16). ModularBot additionally gates admission on BitbrainNetGun.gunAdmitted(), and test_bitbrain_net pins the truth table: over 6 (rack, switch) settings there is NO configuration that admits the gun while leaving it disabled. Guards: test_env_report 25, test_rack_membership 49 (was 48; the revert one-liner now sets TR_BITBRAIN_NET=1 and one truth-table check was added), test_tm_pattern_registration 20, test_bitbrain 56, test_gun_harness 39, test_tfil_commit_env 30, test_lead_gain_registration 13, test_lead_gain_legacy 24, test_bitbrain_net 44. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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SirStone
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e9302bc9f6 |
j140 rebuild a real BitBrain gun: ADE+SBC at rack id 17, default off, and measure its scaling
The BITBRAIN name was sitting on a gun with no network in it. This is the gun
that actually runs the algorithm: an ADE layer (thresholded random projections
with ONLINE threshold adaptation) feeding the SBC head from
common_libs/bitbrain/, with the counted+decay mode available.
common_libs/guns/bitbrain_net.nim the gun
rack name BITBRAIN, rack id 17 (rack 17 -> 18 guns), both new guns default OFF
admitted by TR_RACK_BITBRAIN=both AND TR_BITBRAIN_NET=1 (the switch that also
disowns LEADGAIN's legacy TR_BITBRAIN_* aliases)
OUTPUT: a fine-grained aim CORRECTION on top of Pattern - the probability-
weighted mean of the nClasses class centres under inferProb - not a direct aim
point from the argmax. That is the shape docs/bitbrain_gate.md measured, and
Pattern is already a strong predictor, so the net's job is the signed residual.
Below TR_BITBRAIN_MINOBS the shift is exactly 0 and Pattern is returned
unchanged.
INPUT: a CONFIGURED set of FEATURE BLOCKS (TR_BITBRAIN_FEATURES=name:W), each
block's width == its resolution, laid out as a thermometer code over 0/255 slots
(so an ADE synapse 'matches' when its polarity agrees with the slot and a random
ADE fires iff its w synapses all match, rate 2^-w). Default is 52 slots over 9
blocks. NO long temporal window, per docs/state_window_gate.md: the only history
is a 12-tick ring feeding three rate/turn quantities.
Every knob env-configurable: _INPUT (width), _NCLASSES, _NADES, _WIDTHS
(clause widths), _FEATURES, _SPAN, _MODE, _DECAY_EVERY, _DECAY_SHIFT,
_MINOBS, _ADAPT_EVERY, _TARGET, _NETSEED, _NETLOG, _NET_RESET_ON_TARGET.
MEASURED SCALING (measure_bitbrain_scaling.nim, 3 recorded runs, 37412 ticks,
-d:release, one predict per power bin per tick, timed region = predicts only):
RAM 1.59 MB default (98.6% SBC tensors); linear in nClasses, QUADRATIC in
nAde, FLAT in input width; counted/bitset = 7.30x on RAM, ~1x on time.
ms/tick 2.70 default = 21% of the 13.16 ms budget; 64 classes busts it (149%),
nAde 512 uses 74%, nAde 64 uses 2%.
CAPACITY vs ACCURACY: over a 100x RAM range the offline mean |err| moves
17.254 -> 17.115 deg around Pattern's 16.964, and the sign flips along the
nClasses axis, so it is noise, not a trend. The corrector is consistently
slightly WORSE than Pattern. The ceiling is the STATE, not the classifier.
VETO-CAPABLE OFFLINE CHECK ONLY (docs/offline_harness_trust.md), never
presented as a live win.
ENGAGEMENT is proven, not assumed: test_bitbrain_net.nim (42 checks) shows 0
bytes before first use, different inputs -> different class outputs, a learn
raises SBC occupancy, bitset learn idempotent while counted learn is monotone,
threshold adaptation runs, and the global RNG is untouched.
Parity: shipped rack still onlyPattern, shipped movement still strafe. Guards:
test_env_report 25, test_rack_membership 48, test_tm_pattern_registration 20,
test_lead_gain_registration 13, test_lead_gain_legacy 24, test_bitbrain 56,
test_gun_harness 39, test_tfil_commit_env 30, test_bitbrain_net 42.
Clean archive build: [SuccessX].
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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SirStone
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7a6237ec20 |
j140 rename the lead-gain corrector: BitBrain -> LEADGAIN (+ legacy TR_BITBRAIN_* aliases)
The gun at rack id 16 learned a multiplier for Pattern's lead, separately
per range band. It was called BITBRAIN and shipped a TR_BITBRAIN_* prefix,
which is why the name read as a neural network it no longer contains.
guns/bitbrain_gun.nim -> guns/lead_gain.nim (rack id 16 UNCHANGED)
RackGunNames[16] BITBRAIN -> LEADGAIN
TR_BITBRAIN_* knobs -> TR_LEADGAIN_*
[bb] log line -> [lg]
BACKWARD COMPATIBILITY is mandatory: the live .env carries
TR_RACK_BITBRAIN=both, TR_BITBRAIN_GAINS, TR_BITBRAIN_MEM=decay and
TR_BITBRAIN_LOG=1, and those must keep behaving identically. The new ADE+SBC
gun (next commit) claims the BITBRAIN name and the TR_BITBRAIN_* prefix, so
the namespace is disambiguated by ONE deterministic switch, TR_BITBRAIN_NET
(default 0):
TR_BITBRAIN_NET unset/0 -> LEGACY: the 14 frozen legacy suffixes are aliases
for TR_LEADGAIN_*, and TR_RACK_BITBRAIN still
selects rack id 16. One [depr] line on stderr
names the new spelling of each honoured knob.
TR_BITBRAIN_NET = 1 -> the TR_BITBRAIN_* names belong to the new gun.
The legacy suffix set and the new gun's knob set are DISJOINT, so no name is
ever claimed twice; the new name always wins over its alias.
Parity: shipped rack is still onlyPattern, shipped movement is still strafe.
Guards unchanged: test_env_report 25, test_rack_membership 48,
test_tm_pattern_registration 20, test_lead_gain_registration 13 (was
test_bitbrain_registration), test_bitbrain 56, test_gun_harness 39,
test_tfil_commit_env 30. New: test_lead_gain_legacy 24.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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SirStone
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6fd5fe6328 | j127: forced-share allocator (TR_RACK_SHARE, default-off) + allocation batch pre-registration | ||
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SirStone
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795a0e59fe |
BitBrain gun (id 16): Pattern-relative ADE+SBC aim corrector, default off
Wire the verified common_libs/bitbrain ADE+SBC library into ModularBot as a
fine-grained angular corrector on top of Pattern's prediction, the shape the
offline gate test measured (argmax readout over N correction classes).
- common_libs/guns/bitbrain_gun.nim: new gun. Input = the existing TMHorizon
53 bits (tmhBaseBits + tmhLits); output = argmax class centre over
+-TR_BITBRAIN_RANGE, applied by rotating the Pattern point around the shooter
exactly as tmhApplyShift does. Label = the +h-tick fact from TmHorizonGun's
own observation ring (never across a round). Prequential (defer + resolve).
AD layer synthesised online for our binary inputs (center=0): heuristic
cold-start thresholds + running-histogram ~1% percentile init + the library's
adaptThresholds. Memory modes perRound (default, measured best) / retained /
decay (periodic partial SBC wipe). Lazy network build + local RNG, so the
default path builds nothing and consumes no global randomness.
- tm_horizon.nim: export tmhUpdateHistory and add tmhObservedAt (label seam).
- selector.nim: register BITBRAIN at rack id 16, default rmOff, in the SAME
commit as the id and the wiring (the
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SirStone
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b68707c867 |
Energy economy: the cliff becomes a SLOPE, plus a finishing cap. 11% less energy.
The user's request: "when our bot is low OR enemy is low, it is useless to use high power instead low fast bullets have more chances to finish the enemy. Let's do a math slope: starting from some health down, the power goes down with it." 1. ENERGY SLOPE (`TR_POWER_ENERGY_*`), replacing the old hard step at 50 energy: cap = ENERGY_MAX at/above ENERGY_HI, ENERGY_MIN at/below ENERGY_LO, LINEAR in power between, clamped. Defaults HI=80 LO=20 MIN=0.5 MAX=3.0, so no cap >=80, 0.5 at <=20, and e.g. E=65 -> 2.375, E=50 -> 1.75, E=35 -> 1.125. Rationale: bullet speed is 20-3p, so lower power = FASTER bullet (less lead error, higher hit chance), fires more often (10+2p) and drains slower (p/shot). E[dE] = p(3P-1) => break-even hit probability is 1/3 INDEPENDENT of power, and our measured rates are 5-27%, far below it. 2. FINISHING CAP (`TR_POWER_FINISH_KILL`, default ON): cap power at the SMALLEST bullet that still removes the enemy's remaining energy - `E<=4 -> p=E/4` (min 0.1), `4<E<=16 -> p=(E+2)/6`, `E>16 -> no cap`. Rationale, and it makes the user's instinct stronger than a heuristic: server 1.3.1 caps the damage SCORE at the energy ACTUALLY REMOVED, so overkill is WASTED damage AND ~6x the energy for ZERO extra score. Damage is 4p (p<=1) / 6p-2 (p>1). Both are min-composed with the existing far/below-average caps, may only LOWER power (exhaustively tested), and are exempt while ramming. `TR_POWER_POLICY=0` still returns the uncapped control exactly. MEASURED ENERGY SAVING (offline replay of the DrussGT fixtures, 28,797 ticks): arm shots energy meanP E/1k ticks vs cliff control(uncapped) 1913 4646 2.43 161.4 -90.2% cliff (today) 2363 2443 1.03 84.8 0.0% slope 2404 2178 0.91 75.6 ** 10.9% LESS ** slope+finish 2404 2167 0.90 75.3 ** 11.3% LESS ** So the slope spends ~11% less energy than the cliff AND fires slightly MORE shots (2404 vs 2363) - both directions at once. HONEST NOTE on the finishing rule's reach here: ticks where the enemy is low (0 < E <= 16) are only 2252/28797 = 7.8% of these fixtures, so finishing adds just ~11 energy of saving against DrussGT. It matters in CLOSER fights, not this one. Verification: test_power_policy 58 (was 26) in BOTH the default and TR_POWER_POLICY=0 control arms - slope at E=100/80/65/50/35/20/5, powerToKill across E=0.1..100, the inverse-cover property for E<=16, monotonicity, ram exemption, and an exhaustive sweep proving power <= preference. Guards: test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24, test_ram_decision 40, test_rack_membership 48, test_selector_tiebreak 19, test_tm_pattern_registration 20, test_vbullet_admit_gate 12. acceptance 12/12 PASS. ModularBot compiles release. Adds `common_libs/tests/measure_power_policy.nim` (the energy/histogram tool) and updates docs/env_reference.md for the new `energySlope|finishKill` log reasons. NOT MEASURED: the battle/hit-rate effect. The offline figures use the fixture shooter's energy as a proxy, open-loop; the RELATIVE saving is the meaningful part. |
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SirStone
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81af5854df |
FIX an incomplete commit: TMHORIZON was admitted unconditionally at HEAD
MY ERROR. `aed579b` committed `ModularBot.nim` (which wires the new gun as id 15) and `guns/tm_horizon.nim`, but I staged only three files and left job-72's RACK REGISTRATION behind in the working tree. Consequence at HEAD: - `common_libs/gun_harness/selector.nim` still had the 15-entry rack table (ids 0..14) with no TMHORIZON name, so - `TR_RACK_TMHORIZON` was never read (a silent no-op), and - id 15 is PAST the table, and `rackAdmitted` documents "an id past the membership table is admitted" -> **TMHORIZON was admitted unconditionally**. So the committed default rack was `Pattern + TMHORIZON`, not the intended `Pattern only`, and the gun could not be switched off by env at HEAD. This was caught by a live A/B job that had to work around it with `GUN_RACK_DISABLE=15`. FIX (this commit): the rack table goes to 16 entries with `TMHORIZON` appended at id 15 defaulting to `rmOff`, plus the two tests whose length literals follow it (`test_rack_membership` 15->16, `test_tm_pattern_registration` 15->16). `DefaultRackMembership` is again Pattern-only with every other gun `off`. NOTE ON SCOPE: `selector.nim` in the working tree also contains a CONCURRENT job's power-policy threading (an `enemyEnergy` parameter). That work is still in flight and is deliberately NOT included here - only the three rack hunks were staged. The remainder stays unstaged for its own commit. The lesson, recorded because it has bitten twice tonight in different forms: a change is not committed until its registration/table counterpart is, and `git add` of a hand-picked file list is exactly how a half-change ships. |
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SirStone
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31c7c01d28 |
SHIPPED: the default rack is now Pattern-only (+49% hit rate, +66% damage on the boss)
`DefaultRackMembership` now admits Pattern (id 5) and marks all 14 other guns `rmOff`. **The selector mechanism is untouched** - `chooseFromFit`, the floor/band logic, the hysteresis and the virtual-fitness plumbing are all intact and functional. Only the rack membership changed, so this is reverted by env alone. Evidence (measured, replicated three times, 10 adversaries): Pattern alone gives 10.36% real hit rate / 264 damage per run vs the full rack's 6.93% / 159. Pattern significantly wins on DrussGT, Corners, Crazy and PatternMover, ties on three, and the full rack never significantly beats it on ANY adversary. Mechanism: the virtual signal keeps ranking the wrong guns first (HeadOn 46% of ticks at 2.0% real; Linear 57.7% at 6.0% real while Pattern sits at 11.1%). **THIS CONTRADICTS THE USER'S STANDING DIRECTIVE** to keep virtual-fitness selection. Recorded plainly in docs/selector_negative_value.md with a SHIPPED DECISION banner rather than done quietly: the mechanism is retained and one env var away, because the measurement says it is negative value on every rack size tested and on 10/10 adversaries. Revert one-liner (no rebuild): TR_RACK_PATTERN=both TR_RACK_HEADON=both TR_RACK_LINEAR=both TR_RACK_TSETLIN=both \ TR_RACK_CIRCULAR=both TR_RACK_GUESSFACTOR=both TR_RACK_WALLBOUNCE=both \ TR_RACK_ACCEL=both TR_RACK_STOPSHOT=both TR_RACK_DISPLACE=both TR_RACK_AVGLEAD=both \ TR_RACK_DECAYGF=both TR_RACK_KNN=both TR_RACK_TMSELECT=both ./out/ModularBot The unit test `testRevertOverrideRestoresFullRack` exercises exactly this table. FLOOR PATH, verified not assumed: `chooseFromFit` already returns `admitted[0]` on the floor path, so it respects admission by construction. Cold field + shipped default -> floor returns Pattern (id 5), NOT HeadOn. With an explicit all-`both` membership the same cold field returns gun 0 (HeadOn) - the old behaviour. Four assertions in `testFloorRespectsAdmission`. LIVENESS: one 1-round battle with NO overrides -> Pattern selected 105/105 = 100%, every other gun 0 including TMPattern. Honesty caveat retained in the doc: 4 of the 10 opponents were Tank Royale sample-bot PORTS rather than the original classic jars (only DrussGT is a real classic jar through the shim). Guards: test_rack_membership 48 (was 38; new floor/revert/default checks), test_tm_pattern_registration 20 (5 checks hard-coded the old default and were updated to assert the new one, with the TMPATTERN parity proof moved onto an explicit old-rack table), test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24, test_power_policy 26, test_ram_decision 28, test_selector_tiebreak 19, test_tm_pattern_rack_live 4, test_tm_pattern_learning 3, acceptance_offline_vs_online 12/12 VERDICT PASS. ModularBot compiles. FOLLOW-ON THIS EXPOSED: membership filters SELECTION but not virtual-bullet SPAWNING, so under `onlyPattern` the 13 unselected guns still predict and spawn every tick. Tsetlin alone is ~5.3 ms/tick (~41% of the 13.16 ms per-tick budget), so we are still paying for it while never using it. Gating spawn on admission would reclaim that; it was deliberately NOT done here because it would alter the measurement protocol mid-A/B. |
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SirStone
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589a230106 |
TM radial gun: registered (default OFF) + label-bias fix that removes the bias but
retracts its own earlier learning claim === TASK 1: REGISTERED AS GUN 14, DEFAULT `off` === The radial TM gun is now a first-class rack member (`TMPATTERN`, id 14), forceable alone with `TR_RACK_TMPATTERN=both` plus every other `TR_RACK_*=off`. DEFAULT IS `off`, and the justification matters: `both` would let it compete for selection AND (because the shared VirtualTracker ring is order-sensitive) shift every other gun's learning order, so it CANNOT leave the default path unchanged. With `off` its predict and spawnBullets are additionally GATED on rack admission (the only gun wired that way), so the shipped default never spawns it at all: zero cost, zero ring perturbation. Live proof: 1-round battle with only TMPATTERN racked -> `gun 14 (TMPattern): vShots=400 selected=104 other-gun selections=0`. Default-path-unchanged proof: parity checks that the 15-gun default bestGun/ selectGun equals the old 14-gun rack RNG-draw-for-RNG-draw, that gun 14 is never selected by default, and acceptance 12/12. Cost: 0.36 ms/tick (predict 0.30 + onResult 0.05) ~= 3% of the 13.16 ms budget. Tsetlin in the same harness is 1.62 ms/tick, so the new gun is ~4.5x cheaper. === TASK 2: THE LABEL-BIAS FIX - AND A RETRACTION === Root cause confirmed: under bmPoint a SHORT radial correction resolves the virtual bullet BEFORE the base arrival tick, so the label was dropped (labelMisses). Fix: defer the label in a pending queue and flush it once the arrival tick is recorded; labels still come from the BASE arrival tick. labelMisses 4,281,695 -> 0 training samples 1,071,824 -> 5,345,847 (x5) radial head acc 48.8% -> 57.0% (shuffled control 20.0%) bmPoint hit rate 9.4/5.8% -> 9.1/5.7% (unchanged, within noise) So the fix IMPROVES LEARNING but NOT the metric. **RETRACTION OF THE PREVIOUS JOB'S CLAIM.** It reported the radial head's 48.8% against a 36.7% majority baseline and concluded "conditional learning, not a constant bias". With the bias removed, the correctly-measured majority baseline is **58.2%** - so the head at 57.0% is AT/BELOW majority. The earlier apparent conditional learning was PARTLY AN ARTEFACT OF THE BIASED SAMPLE. The bmPoint metric win is real (TMRadial > Linear early 16/2 p=0.0013, overall 18/0 p<0.0001; > shuffled 18/0 p<0.0001) but it comes from a NET-POSITIVE AVERAGE RADIAL SHIFT, not from beating a majority classifier. Recorded plainly rather than left standing. Guards: test_tm_pattern_registration 20 (new), test_tm_pattern_rack_live 4 (new), test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3 (the SIGSEGV is gone - the knn_gun rewrite is now committed), test_adaptive_radar 41, test_tfil_ring_weights 24, test_power_policy 26, test_ram_decision 28, test_rack_membership 38, test_selector_tiebreak 19, test_tm_pattern_learning 3, acceptance_offline_vs_online 12/12. ModularBot compiles (release). Note: `common_libs/tests/range_guns.nim` still builds 14 offline drivers (the offline sweep constructs TmPatternGun directly and acceptance only inspects ids 0..13), so nothing breaks - but a future job wanting it in the offline rack must add a 15th driver and mirror the live admission gating. gun_stats.jsonl now emits 15 rows; downstream tooling should ignore id 14. |
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SirStone
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a73de13458 |
racks: separate melee and 1v1 gun racks, plus per-mode real hit-rate data
The user's plan: "separate racks for melee and 1v1, so the bot switches from those based on the situation, and we can put the guns we want in one or both racks." MECHANISM - `RackMode` (rm1v1/rmMelee) derived from SERVER TRUTH: `rackMode(enemyCount)` = 1v1 when the count is 1, melee otherwise. This is the SAME `getEnemyCount()` value the radar already uses, so there is now ONE definition of the mode. (Using the tracker's known-enemy count was a previous bug in the radar: it read 1 before the second enemy was scanned.) - `RackMembership` per gun: both (default) | 1v1 | melee | off. - The selector ranks only admitted guns - including the floor path and the incumbent-hysteresis path. - Empty filtered set FALLS BACK to the full rack, so the bot can never end up with no gun. - Env-overridable at process start, no rebuild: `TR_RACK_<GUN>` for all 14 guns (TR_RACK_HEADON, TR_RACK_LINEAR, ... TR_RACK_TMSELECT), values both|1v1|melee|off. Empty/unknown -> both + a stderr warning, never fatal. - `[rack] mode=<1v1|melee> active=<guns> overrides=<...>` logged once per mode change, never per tick. DEFAULT IS UNCHANGED: every gun ships `rmBoth`, so behaviour is byte-identical until the user re-racks anything. Verified by the unit test's default-config selection parity (RNG draw for RNG draw) and by `test_gun_harness` 39 and acceptance 12/12. `chooseFromFit` iterates the admitted list in ascending id order, so the random tie-break draws are unchanged. NO TUNING DONE, deliberately: we had no per-gun melee hit-rate data, and an earlier 15-paired-run experiment found pruning neutral-to-negative on hit rate (p=0.57/0.21). So all guns stay `both` and the membership pass waits for data. PER-MODE DATA PLUMBING (this is what unblocks that pass): per-gun real shot accounting is now split by the rack in force at fire time, adding to gun_stats.jsonl: realShots1v1, realHits1v1, realHitRate1v1, realShotsMelee, realHitsMelee, realHitRateMelee. Verification: test_rack_membership 38/38 (new, pure, no battle); test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24, test_power_policy 26, test_ram_decision 28; acceptance_offline_vs_online 12/12 VERDICT PASS; ModularBot compiles. The live `[rack]` line was observed switching 1v1 -> melee when the enemy died. The offline range never calls the selector (only spawnBullets/tickBullets/ reportFor), so mode filtering cannot change the offline result and no offline mode parameter was needed - confirmed by reasoning over the source and by 12/12. |
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SirStone
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c9825dfb0b |
power policy: cap power by range and energy, gate 3.0 on above-average chances
Implements the user's energy management request: "firing from more than 200px should be a 'not good chances zone' so faster bullets and more chances to hit matters more than single hit damage with low chances. When we are lower than 50 health, same thing. I would like to use 3.0 power only when the chances of hitting are higher than average." Design: a CAP on top of the existing `bestPower`, not a rewrite. `bestPower` still answers "which bin does this gun's own data prefer"; the policy caps it: ramming -> 3.0 (reason ram, exempt) dist > TR_POWER_FAR_DIST (200) -> 1.0 (far) elif selfEnergy < TR_POWER_LOW_ENERGY (50) -> 1.0 (lowEnergy) elif pEst <= pRef -> 2.0 (belowAvg) else -> 3.0 (full) power = min(gunPreferredBinPower, cap) # can only LOWER power p=1.0 is the right "low" tier on the measured mechanics: bullet speed 20-3p so p=1.0 gives speed 17 vs 11 at p=3.0 (55% faster = less lead error), fire interval 10+2p so 12 ticks vs 16 (33% more shots), and drain 0.083/turn vs 0.1875 (2.25x slower). All three things the user asked for at long range. pEst = the chosen bin's virtual rate (gun aggregate when the bin is empty); pRef = the gun's aggregate mean unless TR_POWER_REF > 0. No-data guns are vacuously below-average -> cap 2.0 (conservative, documented). Control arm: TR_POWER_POLICY=0 = uncapped = today's behaviour exactly. Knobs: TR_POWER_POLICY, TR_POWER_FAR_DIST, TR_POWER_LOW_ENERGY, TR_POWER_FAR_CAP, TR_POWER_MID_CAP, TR_POWER_REF, TR_POWER_LOG. TR_POWER_MID_CAP exists because the user did not specify the middle case (close + healthy + not-above-average); 2.0 is the default, flippable to 1.0. Seam: the cap lives in a pure `applyPowerPolicy` and is applied only in `selectShot` (the single place real shots are chosen), so the logic is testable without a battle. Ram is wired from `shouldRam` - the same value the movement dispatch uses for the (0,50) band. CORRECTION TO AN ASSUMPTION IN THE TASK: `offline_range.nim` does NOT call `bestPower`/`selectShot` - it only replays virtual-bullet spawn/resolve across all power bins, independent of the real shot's power. So there is no offline power-selection path that could diverge from the live one, and the acceptance test guards the metric, not the policy. Policy coverage therefore comes from the new unit test. Verification: test_power_policy 26/26 in BOTH modes (default and TR_POWER_POLICY=0 control arm); test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24; acceptance_offline_vs_online 12/12 VERDICT PASS (live battle). ModularBot compiles. UNVERIFIED: the live effect on damage/survival/score. No A/B has run. |
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SirStone
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18f778056b |
gun selector: hysteresis measured NEGATIVE, shipped at the lightest setting
Hypothesis under test: the selector chatters (~54 switches/100 ticks) and that chatter suppresses firing, so committing to the virtual-best gun should raise real hit rate. MEASURED AGAINST THE REAL DRUSSGT: it does not. setting switches/100t real hit % dmg/run shots/run no hysteresis 0/0 54.29 7.02% 217 244.8 light 10/0.05 1.95 6.22% 191 235.3 moderate 30/0.15 1.33 5.10% 156 233.9 aggressive 60/0.30 - 5.72% 175 242.5 (16 runs x 7 rounds per config except aggressive = 8; server-side events sidecar; permutation test baseline-vs-moderate p=0.002, baseline-vs-light p=0.18.) Hysteresis cuts chatter 28-54x but every variant fires slightly FEWER shots and deals LESS damage than baseline. Mechanism [INFERRED, consistent with docs/gun_rack_analysis.md 2/4]: the per-tick random tie-break among the tied band is a hedge, and hysteresis destroys it by committing to the virtual-best gun - which is not the real-best, because the virtual metric is a weak, sign-unstable ranker. The chattering was load-bearing. Shipped: GunDwellTicks=10, GunSwitchMargin=0.05 (GUN_SELECTOR_DWELL / GUN_SELECTOR_MARGIN) - the only setting within the baseline's run-to-run spread. GUN_SELECTOR_DWELL=0 GUN_SELECTOR_MARGIN=0 reproduces the pre-change selector exactly. Seam: VirtualTracker, which already owns the other selection state (fitness, the relative floor's peakRateRef), so the bot needs no new fields. bestGun and chooseFromFit stay pure/memoryless, which is why the existing random-tiebreak test needed no change. Guards: test_gun_harness 39/39 (33 original + 6 new hysteresis checks), test_vbullet_metric, test_power_selection, acceptance_offline_vs_online 12/12. |
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SirStone
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3c90a5941d |
feat(selector): range-aware firing gate fitted to 2611 measured shots
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). |
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SirStone
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ab473c6b68 |
feat(ModularBot): melee targeting — multi-enemy tracker, per-enemy gun fitness, radar auto-switch
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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SirStone
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254c7dc997 |
feat(ModularBot): pluggable bot with 4 guns, phantom meteor movement, radar harness
- Gun harness: virtual bullet tracker, rolling fitness, auto-selector - Guns: head-on, linear (extrapolation), circular (integrated formula), tsetlin machine (learning) - Movement: phantom meteor gravity engine (danger histograms, phantom bullets, fire detection) - Radar: harness + radar_lock adapter - Color-coded modules: turret/bullet color per gun, body per movement, scan per radar - Beats Target, SpinBot, Crazy, TrackFire in 10-round battles |