🔬

Self-confirming price-prediction strategies for simultaneous one-shot auctions.

📅 2017
technical research breakthrough
🔵 Rare

📖 Description

Self-Con?rming Price Prediction Strategies for Simultaneous One-Shot Auctions Michael P. Wellman Computer Science & Engineering University of MichiganEric Sodomka Computer Science Brown UniversityAmy Greenwald Computer Science Brown University Abstract Bidding in simultaneous auctions is challeng- ing because an agent?s value for a good in one auction may depend on the uncertain outcome of other auctions: the so-called exposure prob- lem. Given the gap in understanding of gen- eral simultaneous auction games, previous works have tackled this problem with heuristic strate- gies that employ probabilistic price predictions. We de?ne a concept of self-con?rming prices , and show that within an independent private value model, Bayes-Nash equilibrium can be fully characterized as a pro?le of optimal price- prediction strategies with self-con?rming predic- tions. We exhibit practical procedures to com- pute approximately optimal bids given a proba- bilistic price prediction, and near self-...

📊 Game Impacts

Not verified in game

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Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

💭 Reactions

🔬 Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Notable work on AI safety"
📰 Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Peer-reviewed publication"
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🔗 Sources

🏷️ Event Metadata

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📁 Category Technical Research Breakthrough → Suggest different category
⭐ Rarity 🔵 Rare → Suggest different rarity
🏷️ Tags (0) → Suggest tag changes
📊 Game Impacts (3) 3 variable changes → Suggest impact changes
☢️ p(Doom) Impact No direct impact → Suggest p(doom) change
📝 General Metadata Year, description, reactions → Comprehensive review

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