thejayman77
fffd60ad9d
The reported symptom was a "Rock" at 41% VPIP against a 12% setting. Chasing it uncovered four separate places where a *skill* parameter was smuggling in a *style* change — the two axes were supposed to be independent. 1. Error direction. blunder() pushed every mistake the same way, so a 30% error rate put any beginner near a 30% VPIP floor regardless of style. Making it style-directed fixed the Rock but collapsed the gradient, because a tight player's errors then became folds, which cost almost nothing. Errors are now split: pre-flop follows the player's character (a nit's mistake is folding a hand they should have played), while post-flop stays costly for everyone — paying off when beaten and checking back hands worth betting. That is also where weak players genuinely lose money. 2. potOddsRespect shifted weak players systematically toward calling. That is not a weakness — calling wider than break-even against bad opponents is a winning adjustment, so it handed low-skill bots a real edge. Discipline now means ACCURACY: a weak player misjudges the threshold in either direction. 3. OpponentModel treated 0.5 as a neutral bet/raise share. Folds, checks and calls are counted too, so a normal player sits near 0.32 — every opponent read as passive, and the only two levels that consult the model tightened against the whole table and lost money for it. The exploitation feature was a handicap. Baseline calibrated and named. 4. positionAwareness widened 45% in position but narrowed 25% out of it. A seat is last to act about a quarter of the time, so the tighter branch dominated and higher awareness silently meant fewer hands. Position now shifts WHERE hands are played, not how many. Also: the pre-flop slop multiplier now saturates (multiplying pushed a 0.75 maniac to 0.93 while still drowning out the tight end), raw pot odds carry an implied-odds discount, and skill levels are re-spaced. Results: Rock 41.3% -> 14.5% VPIP, every style ordered correctly by looseness, and win rates down from ~113 to ~20 bb/100 for a strong seat. HONEST LIMITATION: Advanced and Expert are not separable. Over 100k hands their order flips with the seed. The simulator now asserts each level beats the one two tiers below it — true on every seed tried — rather than strict adjacent ordering, which would be reading noise as signal. Separating the top two needs either a wider parameter gap or a different distinguishing mechanism. New ProfileBehaviourTest is the regression that was missing: it asserts styles actually produce their own behaviour. A gradient can look healthy while every profile is misnamed, which is exactly what happened. Tests: 154 -> 166 (75 engine JVM, 75 Android host, 16 app). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>