Fix consumer subscription pricing exploit with perceived-value-based elasticity

Players could set astronomical prices and still retain subscribers because
price elasticity floored at 10% for any price above $100, satisfaction
ignored pricing entirely, and churn had no price component.

Introduces perceived value per tier (model quality × reputation), replaces
the broken linear formula with sigmoid decay, adds price-aware satisfaction
blending, and applies per-tier price-based churn multipliers.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

packages/game-engine/src/systems/market/tamSystem.ts

@@ -15,6 +15,8 @@ import {
   ATTRACTIVENESS_WEIGHTS,
   OBSOLESCENCE_PENALTY_WEIGHT,
   NEW_MODEL_BOOST_VALUE,
+  CONSUMER_TIER_BASE_PERCEIVED_VALUE,
+  PERCEIVED_VALUE_REPUTATION_RANGE,
 } from '@ai-tycoon/shared';
 
 export interface ParticipantProfile {
@@ -27,6 +29,16 @@ export interface ParticipantProfile {
   hasFreeTier: boolean;
 }
 
+function computeTamPriceScore(price: number, qualityScore: number, reputation: number): number {
+  if (price <= 0) return 1;
+  const repRange = PERCEIVED_VALUE_REPUTATION_RANGE;
+  const repMult = repRange.min + (Math.max(0, Math.min(100, reputation)) / 100) * (repRange.max - repRange.min);
+  const refPV = CONSUMER_TIER_BASE_PERCEIVED_VALUE.plus * qualityScore * repMult;
+  if (refPV <= 0) return 0;
+  const ratio = price / refPV;
+  return 1 / (1 + ratio * ratio);
+}
+
 export function buildPlayerProfile(
   qualityScore: number,
   chatPrice: number,
@@ -36,8 +48,7 @@ export function buildPlayerProfile(
   obsolescence: ObsolescenceState,
   hasFreeTier: boolean,
 ): ParticipantProfile {
-  const avgPrice = (chatPrice + apiOutputPrice) / 2;
-  const priceScore = Math.max(0, Math.min(1, 1 - avgPrice / 100));
+  const priceScore = computeTamPriceScore(chatPrice, qualityScore, reputation);
 
   let freshness = obsolescence.playerModelFreshness;
   if (obsolescence.newModelBoostRemaining > 0) {
@@ -56,8 +67,8 @@ export function buildPlayerProfile(
 }
 
 export function buildCompetitorProfile(c: Competitor): ParticipantProfile {
-  const avgPrice = (c.products.chatPrice + c.products.apiOutputPrice) / 2;
-  const priceScore = Math.max(0, Math.min(1, 1 - avgPrice / 100));
+  const compQuality = Math.min(1, c.estimatedCapability / 100);
+  const priceScore = computeTamPriceScore(c.products.chatPrice, compQuality, c.reputation);
 
   return {
     id: c.id,