SirRoboGarage/tools/fixtures/TR_BRIDGE_FIXTURES.md

Tank-Royale bridge fixtures — DrussGT vs our bots (closed loop at capture time)

Fixtures captured from real Tank Royale battles in which the real, unmodified classic DrussGT 3.1.4159 plays through the Java bridge in tools/robocode_shim/, against opponents whose shots it actually had to dodge. They complement the classic-Robocode set in DRUSSGT_FIXTURES.md.

Why these exist — the fidelity gap they close

DRUSSGT_FIXTURES.md documents two gaps in the classic captures:

1. Open loop. Replayed DrussGT never dodges our bullets, so our gun scores optimistically against it.
2. Perfect information. The observer reports true positions every tick, unlike the live bot's stale between-scan WorldState.

These TR-bridge fixtures close gap 1, at capture time: the recorded trajectory is one in which DrussGT was actively reacting to our bot's real bullets (ModularBot's gun) in Tank Royale physics. The coupling is measured in Closed-loop evidence below.

Gap 2 remains. These are still observer captures: true positions every tick, no fog of war, no sensor latency. They are therefore optimistic relative to live play. And because a fixture is a recording, replaying it against a different gun is still open-loop — the closed loop exists only in the battle that produced the file, not at replay time.

Provenance / capture mechanism

• Bot host: tools/robocode_shim/ (DrussGTBridge + ClassicPeer). See the shim README §5 for the physics/API details and §5.9 for the known divergences.

• Observer: tools/robocode_shim/src/robocode_shim/TrBattleCapture.java, which runs the Tank Royale battle-runner API (embedded server) and writes the shared JSONL format, plus a .rounds.json sidecar and a raw .results.json.

• Commands (shield off unless stated):

  tools/robocode_shim/run_bridge_battle.sh \
      /tmp/capture_bots/ModularBot 15 /tmp/cap/tr_drussgt_vs_modularbot.jsonl
  # TR_EVENTS_OUT=... adds the bullet-event sidecar used for the loop analysis
  

• DrussGT runs as the pure wave surfer (DrussMoveGT), i.e. the EnergyDome shield is disabled (DRUSSGT_SHIELD unset). DRUSSGT_SHIELD=1 was used only for the _shield file. The ModularBot binary is a frozen snapshot (md5 d39dbdc326132cd371cd12f97bfb0a16) copied to /tmp; no Nim build was invoked during capture.

Format

Same field layout as the classic fixtures (ex/ey/eh/es/ee, sx/sy/sh/ss/se, continuous global tick), but the meta line is distinct:

{"meta":{"adversary":"ModularBot","source":"tr-bridge","closed_loop":true,
         "perfect_info":true,"arena":{"w":800,"h":600},"note":"..."}}

source is "tr-bridge" (classic files say "classic-robocode"), closed_loop is true, and the note states the capture-time loop and the remaining open-loop/perfect-info caveats. e* is always DrussGT; s* is the adversary. Round boundaries are in drussgt_meta/<file>.jsonl.rounds.json; per-round running scores are in drussgt_meta/<file>.jsonl.results.json.

Files

File	rounds	ticks	bytes	adversary	shield
tr_drussgt_vs_modularbot.jsonl	15	20,026	2,976,439	ModularBot (our bot)	off
tr_drussgt_vs_modularbot_shield.jsonl	10	12,629	1,872,874	ModularBot	on
tr_drussgt_vs_spinbot.jsonl	10	10,824	1,597,273	sample SpinBot	off
tr_drussgt_vs_crazy.jsonl	10	11,507	1,701,186	sample Crazy	off
tr_drussgt_vs_corners.jsonl	10	2,575	379,680	sample Corners	off

The primary benchmark is tr_drussgt_vs_modularbot.jsonl (shield off): 20,026 ticks over 15 rounds, mean 1,335 ticks/round (min 845, max 1,893). The rounds are not short — DrussGT does not trivially rush ModularBot — so ModularBot generated a real shot stream: 1,134 shots in that run.

Movement statistics vs the classic captures

Produced by tools/robocode_fixture_capture/analyze.py (values are fractions, median range in px). Classic rows are copied from DRUSSGT_FIXTURES.md.

fixture	mean speed	full ≥7.5	rest <0.5	neg. vel	mean |Δh|	|Δh|>5°	median dist	perp frac	radial frac	mean|sin|
TR modularbot	5.922	0.528	0.037	0.463	1.629	0.109	463.9	0.967	0.001	0.971
TR modularbot (shield)	5.826	0.533	0.070	0.466	1.574	0.097	450.0	0.959	0.001	0.967
TR spinbot	6.981	0.749	0.019	0.487	1.596	0.091	443.2	0.982	0.001	0.979
TR crazy	7.040	0.767	0.019	0.413	2.035	0.094	423.1	0.883	0.005	0.946
TR corners	6.954	0.770	0.037	0.489	2.158	0.111	524.5	0.883	0.026	0.941
classic spinbot	6.59	0.701	0.067	0.464	1.81	0.094	402	0.962	0.001	0.971
classic crazy	6.16	0.668	0.137	0.439	2.01	0.083	378	0.829	0.010	0.934
classic corners	6.01	0.586	0.092	0.419	2.09	0.125	504	0.920	0.004	0.964
classic drussgt (mirror)	5.26	0.411	0.066	0.457	1.29	0.082	526	0.951	0.001	0.972

The wave-surfer signature — strongly perpendicular to the opponent (perp frac 0.88–0.98), near-zero radial fraction, ~41–49% reversals, near-full speed — is present in the TR captures and matches the classic set closely (perp/radial within ~0.04 of the matching classic opponent). The TR runs are slightly faster and shorter-ranged, as before, because the rounds are shorter and the shield is off. This is surfing, not a straight line or a stall.

Battle outcomes

DrussGT vs ModularBot, 15 rounds, shield off: DrussGT 1447 – 300, 14 rounds won (ModularBot won round 5). Per-round ticks and running scores:

round	ticks	DrussGT score	ModularBot score	winner
1	1252	71	8	DrussGT
2	1416	152	20	DrussGT
3	845	286	36	DrussGT
4	1446	385	68	DrussGT
5	1893	399	156	ModularBot
6	1080	499	156	DrussGT
7	1460	606	188	DrussGT
8	1213	708	200	DrussGT
9	1759	808	228	DrussGT
10	1380	910	236	DrussGT
11	1127	1026	252	DrussGT
12	1258	1144	272	DrussGT
13	1330	1240	280	DrussGT
14	1474	1336	292	DrussGT
15	1093	1447	300	DrussGT

Scores are the server's cumulative running totals at round end. DrussGT: 1400 bullets / 169 hits / 60 hits taken. ModularBot: 1,134 bullets / 60 hits / 169 hits taken; 29 bullet-bullet.

Adversaries (shield off, 10 rounds each): SpinBot 1175–0, Crazy 1080–1, Corners 1659–0; all 10 rounds won in each. ModularBot shield on, 10 rounds: DrussGT 939–287, 9 rounds won (ModularBot won round 1).

Closed-loop evidence

Claim under test: at capture time DrussGT's movement is coupled to ModularBot's live fire, not an independent open-loop trajectory. Measured with tools/robocode_shim/analyze_closed_loop.py on tr_drussgt_vs_modularbot.jsonl + tools/robocode_shim/evidence/tr_drussgt_vs_modularbot.events.json:

python3 tools/robocode_shim/analyze_closed_loop.py \
  tools/fixtures/tr_drussgt_vs_modularbot.jsonl \
  tools/robocode_shim/evidence/tr_drussgt_vs_modularbot.events.json

What the run establishes (numbers from that exact run):

• ModularBot fires on an exogenous, heat-limited clock. Fire interval median 14 ticks (p10 14, p90 20). It is a near-metronome, so it is not following DrussGT tick-by-tick.
• DrussGT's turning is strongly phase-locked to ModularBot's fire ticks. Event-locking |Δheading| to the adversary's fire times gives an oscillating response (dips ≈0.96–1.35°, peaks ≈2.1–2.7° about a ≈1.47° mean) with the fire period (~13–14 ticks). With 15 rounds, 1,134 fires, almost every lag is outside the 95% band of a null that circularly shifts each round's fire times (permutation null). The peaks are the surf re-committing on each new enemy wave (fire detection); the lulls are the committed run between waves.
• The lock is enemy-specific, not an internal clock. The same analysis locked to DrussGT's own fire times is essentially flat (only lag 0 is marginally outside the null). So the oscillation is driven by the incoming fire, not by DrussGT's own gun cadence.
• Cross-correlation |Δheading| vs fire impulse: peak r = +0.111 at lag 12 ticks, permutation p = 0.005 (null peak mean +0.016, max +0.028). Reversal rate: peak r = +0.025 at lag 29, p = 0.035.
• Range keeping responds weakly. Mean range rises monotonically from 478.3 px at the fire to 481.7 px 30 ticks later — a ~3 px drift, near the noise floor, so it is not claimed as strong evidence.

Honest reading. The PSTH and cross-correlation are significant against a phase-shuffled null and are absent in the own-fire control, so DrussGT's movement is temporally coupled to ModularBot's firing at capture time. The effect size is modest (peak r ≈ 0.11) — expected, because DrussGT surfs almost all the time regardless, and the lock is modulated by the periodic wave train. What is not shown is that each individual bullet is dodged on approach: the shield (which detects individual bullets) is off here, so the coupling is the wave-level reaction to the enemy energy drop / fire, which is exactly how this surfer decides to move. No claim is made beyond that.

Caveats

1. PERFECT INFORMATION. Observer captures report true positions every tick; the live bot's WorldState is stale between radar scans. Optimistic vs live play.
2. OPEN LOOP AT REPLAY TIME. These are recordings. DrussGT reacts to ModularBot's bullets in the file that was captured, not to whatever gun later replays the trajectory. The closed_loop:true flag describes the capture, not the replay.
3. Physics divergences from classic Robocode remain (move/turn ordering, distance bookkeeping, no exact trajectory equivalence). See the shim README §5.9. The classic captures validate to 0.000°; TR converts at ~1.5° mean (median ~0.05°) because of the engine's pre-turn move ordering.
4. The shield-on file is included for completeness; its round 1 is the known shield warm-up case (shorter, more stationary) — the shield-off files are the primary set.
5. No round in these captures aborted or timed out; every round ended in a death (see winners table).