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원본 프로젝트 animatedread/Warrior_EA
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6 commits

작성자 SHA1 메시지 날짜
AnimateDread
a4af9313d4 chore(settings): update settingsh1.set configuration 2026-07-16 19:25:26 -04:00
AnimateDread
0bfc441139 feat: real-ZigZag training labels, HYBRID CPU-oversubscription fix, input cleanup
- Replace the hand-rolled fractal/deviation-%/ATR-trend-context ZigZag
  approximation with the actual MQL5 ZigZag indicator (rebranded as
  CustomIndicators/ADZigZag.mq5, logic untouched) as the training label
  source; bump the settle/confirmation window from 20 to 100 bars so a
  proper leg can form before being trusted, and drop the now-dead
  ZigZagDeviationPct/MinTrendATRMultiple/TrendContextBars inputs.
- Rebrand the stock Volumes indicator the same way (ADVolume.mq5).
- Fix HYBRID mode (AIType=HYBRID) oversubscribing the CPU fallback tier:
  every concurrent CNet instance was independently sizing its worker
  pool off the same global TargetCPULoad input. g_netPeerCount/
  PeerNetworkCount() now split it across however many CNet instances
  (live+shadow x active signals) are actually sharing the CPU.
- Fix NEURONS_REDUCTION_FACTOR's confusing retention-vs-reduction
  semantics so RF_70 means an actual 70% reduction; default to 4 hidden
  layers / RF_70.
- Migrate remaining free-form training/indicator inputs to enums for UI
  consistency; default news filter lookback to 1h, disable every-tick.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-16 00:56:33 -04:00
AnimateDread
8c66a0fb89 fix(cl): stabilize network training with tighter limits, weight decay, and sign-agreement gate
- Tighten MAX_WEIGHT from 1.0e6 to 100.0 to prevent unbounded weight growth.
- Add MIN_ACTIVATION_DERIVATIVE (1e-4) to avoid zero gradients for saturated units.
- Introduce WEIGHT_DECAY (0.01) to decouple decay from Adam updates.
- Add MAX_WEIGHT_DELTA (0.1) to clamp per-step Adam updates and prevent overshoot.
- Apply sign-agreement gate on weight updates in Adam kernel to only apply steps aligned with current gradient direction.
- Fix tanh/sigmoid derivative calculations to use the new floor instead of hard-coded edge-case values.
2026-07-15 21:47:37 -04:00
AnimateDread
068495b3d7 fix: clean up EA init/deinit lifecycle and close a DirectML mutex-poisoning hang
Warrior_EA.mq5: clear Comment() and destroy the control panel before
Expert.Deinit()'s object-purge cascade runs out from under it; stop
re-registering the same signal filters on every DB retry (was causing a
double-delete of the same pointer on shutdown).

DirectML/WarriorCPU.cpp: bound the worker-thread join in ThreadPool::Stop()
instead of blocking forever - CPU_Shutdown() held g_mutex across an unbounded
join, so a watchdog-killed calling thread could leave it locked forever,
poisoning every future call into the DLL (matches reports of the EA getting
stuck on "initializing" after being removed and re-added to a chart).

Also includes prior era-0 label-cache prebuild and pullback/reversal
label-quality work in AI/Network.mqh, Expert/ExpertSignalAIBase.mqh, and
Variables/Inputs.mqh.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-14 22:36:27 -04:00
AnimateDread
1204b9df97 feat: add percentage-based CPU load input for fallback tier
Replace the absolute thread count input (CpuDllThreads) with a percentage-based CPU_LOAD_PRESET enum (TargetCPULoad). This allows users to specify a percentage of detected cores to use when the CPU DLL fallback is active, improving flexibility and preventing issues when multiple instances share the same CPU DLL pool. Also adds CPU_GetHardwareConcurrency() for accurate core detection.
2026-07-14 18:04:48 -04:00
AnimateDread
9464e52784 feat: embed compute DLLs as resources and extend Save/Load for training state
Add #resource directives for WarriorDML.dll and WarriorCPU.dll, and ExtractComputeDlls() to extract them on first run, enabling MQL Cloud Protector builds to ship DLLs without manual copy. Extend CNet::Save and Load with trainingComplete and indicatorParams arrays to persist AutoTune indicator param values.
2026-07-13 15:59:35 -04:00