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fix: supra reward adjustment and sweep

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This commit is contained in:
Daniel Rosel
2026-03-16 15:58:05 +01:00
parent 43b952cf2b
commit 3439775fbd
4 changed files with 103 additions and 8 deletions
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29
engine/wrapper.py
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@@ -216,18 +216,27 @@ class PHANTOM(gym.Env):
coi_penalty = self.lambda_coi * coi_leakage * info_budget
if len(self._price_history) > 0:
volatility = float(
np.mean(
np.abs(prices - self._price_history[-1])
/ np.maximum(self.baseline_prices, 1.0)
)
)
prev_prices = np.asarray(self._price_history[-1], dtype=float)
rel_change = (prices - prev_prices) / np.maximum(prev_prices, 1.0)
volatility = float(np.mean(np.abs(rel_change)))
upward_volatility = float(np.mean(np.clip(rel_change, 0.0, None)))
else:
volatility = 0.0
ux_penalty = self.eta_ux * info_budget * volatility
upward_volatility = 0.0
ux_penalty = self.eta_ux * info_budget * (volatility + 0.5 * upward_volatility)
competitive_anchor = float(
np.clip(float(self.human_params[0]) * 1.2, *self.price_bounds)
)
price_ratio = prices / max(competitive_anchor, 1.0)
supra_excess = np.clip(price_ratio - 1.0, 0.0, None)
supra_penalty = (
0.5 * self.eta_ux * info_budget * float(np.mean(np.square(supra_excess)))
)
supra_share = float(np.mean(supra_excess > 0.0))
reward_revenue = self.reward_profit_weight * profit
reward = reward_revenue - coi_penalty - ux_penalty
reward = reward_revenue - coi_penalty - ux_penalty - supra_penalty
return reward, {
"revenue": revenue,
@@ -240,6 +249,10 @@ class PHANTOM(gym.Env):
"coi_info_budget": info_budget,
"ux_penalty": ux_penalty,
"volatility": volatility,
"upward_volatility": upward_volatility,
"supra_penalty": supra_penalty,
"supra_share": supra_share,
"competitive_anchor": competitive_anchor,
"reward_revenue": reward_revenue,
"reward_total": reward,
}