Fleet template is now rebuilt only when deploymentVersion changes (~68 times per
28,800-tick run instead of every tick). Reuses module-level Maps, arrays, and
utilization objects instead of allocating new ones each tick. Replaces 4x
Object.values().reduce() with single-pass aggregation and sorts fleet in-place.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Switch from exec() to spawn() for streaming stderr, add onProgress
callback to runner, and emit per-run progress lines from workers.
CI now shows live percentage, tick count, and era during long runs.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Research now costs money (drained per-tick) with ~2.5-3.5x longer durations by category.
Early-game talent budget costs reduced via era multiplier (startup 0.2x → bigtech 1.0x).
New seed-driven PersonaStrategy with 8 axes of variation for meaningful multi-run testing.
CI multi-run switched from greedy to persona strategy.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove misleading Reputation -> Era Gates connection (score 0 meant
"already sufficient," not broken). Add diagnosis and eventLabel fields
to each connection. Group output: broken links first with [!!] and
plain-language explanation, then healthy links as compact one-liners.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds a full simulation harness (game-simulation package) with greedy/random strategies,
36-metric diagnostics, multi-run orchestration via child processes, and a statistical
interpreter. Includes 2.3x engine performance optimizations (research bonus caching,
per-DC dirty tracking, reduced allocations in tick pipeline, single-pass loops).
Fixes a critical balance bug where training pipelines stalled on insufficient VRAM would
permanently block training slots — the engine never re-checked stalled pipelines, and the
greedy strategy didn't pre-check VRAM requirements. This caused 20-25% of seeds to get
stuck in Scale-up era. All three fixes (engine un-stalling, strategy VRAM pre-check,
stalled pipeline cancellation) bring pass rate from 75% to 100% across 20 random seeds.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
josh