Commit Graph

3 Commits

Author SHA1 Message Date
thejayman77 0ac69b101a Replace bot tuning guesses with enforced calibration 2026-07-26 05:13:54 -04:00
thejayman77 7f82251d86 Android target, suspending agents, and observable table snapshots
Build:
- :engine now uses com.android.kotlin.multiplatform.library (AGP 9.2.1), the
  modern KMP Android integration, rather than plain androidTarget(). Produces
  engine.aar alongside the JVM target; compileAndroidMain verified.
- Version catalog added; SDK levels match the other JSJ apps (compileSdk 37,
  minSdk 26).

Engine:
- PlayerAgent.act() and Table.playHand() are now suspend, so a human player can
  wait for input without blocking a thread. Bots are unaffected; the simulator
  wraps in runBlocking.
- TableSnapshot/SeatSnapshot published after the deal, before and after every
  action, and at the finish. Immutable, aliasing no live Seat state, giving
  animation, hand history, saving, and replay one boundary to work against.
- Snapshots carry the whole truth; maskedFor(viewer) is an explicit step that
  hides hole cards the viewer is not entitled to. Showdown reveals contenders;
  folded hands never are.
- Terminal snapshots report the contested pot rather than 0. settle() zeroes
  contributions when awarding, so the naive value was empty at exactly the
  moment the UI needs to show what was won. Caught by a new test.
- HumanAgent suspends on a CompletableDeferred and clears its pending state in a
  finally block, so cancelling an abandoned hand releases the wait instead of
  stranding it. Re-usable afterwards; a stale submit returns false.

Tests: 37 -> 45. Chips still conserved, skill gradient still monotonic.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-07-25 10:55:28 -04:00
thejayman77 479be1f6b9 Initial commit: Hold'em engine, bots, and simulation harness
Kotlin Multiplatform engine (JVM target only for now; androidTarget and
iosArm64 slot in without touching commonMain).

Core:
- HandEvaluator: single-pass 5-7 card evaluation, ~24M evals/sec. Verified
  exhaustively against published frequencies for all 2,598,960 five-card hands.
- Equity: Monte Carlo with ties split. PreflopChart ranks the 169 starting
  hands using all-in equity plus an explicit playability adjustment, so
  looseness means "plays the top N%".
- Table: no-limit betting rounds, side pots, odd-chip splits, uncalled-bet
  refunds, and incomplete (short all-in) raises that correctly do not reopen
  betting.

Bots:
- SkillLevel and PlayStyle are orthogonal axes. Skill drives decision quality
  (rollout accuracy, pot-odds discipline, position awareness, error rate);
  style drives bluffing, sandbagging, aggression, tightness.
- BotMood gives tilt that persists between hands and decays.
- OpponentModel lets Advanced/Expert exploit habitual bettors.
- MathBot emits a DecisionTrace of the numbers behind each decision, which the
  coach will later hand to an LLM to narrate. The LLM never does poker maths.

Simulator:
- 2,200-3,400 hands/sec. Deck RNG is separate from bot RNGs so rollout counts
  cannot shift the deal.
- Controlled skill-ladder test asserts the difficulty gradient is monotonic:
  73.9 / 53.9 / 27.6 / -155.4 bb/100 over 50k hands.

Assets: 52 CC0 English-pattern card faces plus generated backs.

Tests: 30 passing (evaluator, table rules, pre-flop chart).

Known open: win-rate magnitudes ~10x realistic and several profiles looser
than their labels. Tuning, not correctness.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-07-25 04:36:03 -04:00