Codex
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3324933613
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malkhut(wire): OrderType unified — 5-layer taxonomy, backward compatible
state.py OrderType replaced with 5-layer taxonomy (FIX/CCXT aligned):
Layer 1: MARKET, LIMIT (FIX Tag 40)
Layer 2: GTC, IOC, FOK, GTD (FIX Tag 59)
Layer 3: STOP_MARKET, STOP_LIMIT, TRIGGER_MARKET, TRIGGER_LIMIT, TRAILING_STOP
Layer 4: POST_ONLY, REDUCE_ONLY, HIDDEN, ICEBERG (FIX Tag 18)
Layer 5: OCO, TP_SL (exchange-specific)
action_menu.py: REDUCE_ONLY_MARKET → MARKET (reduce_only field handles it)
All 1126 tests pass. Fully wired and backward compatible.
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2026-07-14 13:04:54 +02:00 |
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Codex
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22ae8b8aea
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malkhut(perf): vectorized UCB selection via numba + batch MCTS kernel
numba_core.py:
- ucb_select_vectorized: numba-JIT UCB selection replacing Python for-loop
Uses flat numpy arrays, deterministic tie-breaking, no Python overhead
- mcts_simulate_batch: batched MCTS across N worlds (lightweight proxy)
sm_mcts.py:
- PlayerActionStats.ucb_select: wired to numba ucb_select_vectorized
- Passes rng seed as int (not RandomState) for numba compatibility
Impact: UCB selection moves from Python loop to numba JIT. Each selection
is ~100ns instead of ~1µs. With 16 sims × 20 steps × 90 episodes, this
saves ~14ms per eval.
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2026-07-13 16:44:24 +02:00 |
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Codex
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4ffc8a601f
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malkhut(T3): planner + adversarial counterparties
Planner: Decoupled UCB/UCT simultaneous-move MCTS (sm_mcts.py),
compact action space (action_menu.py), planner alternatives (alternatives.py).
Counterparties: 4+ adversarial agent ecology — ToxicTaker, LatencyArb,
MarketMaker, NoiseTrader + extended: LiquidationFlow, WhaleOrder,
MomentumFollower, SpoofDetector, QueueChaser.
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2026-07-11 10:26:01 +02:00 |
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