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Iterative combinatorial auctions: achieving economic and computational efficiency
iBundle is proposed, an iterative combinatorial auction in which agents can bid for combinations of items and adjust their bids in response to bids from other agents, and also compute Vickrey payments at the end of the auction.
Iterative Combinatorial Auctions: Theory and Practice
iBundle is introduced, the first iterative combinatorial auction that is optimal for a reasonable agent bidding strategy, in this case myopic best-response bidding, and its optimality is proved with a novel connection to primal-dual optimization theory.
Optimal auctions through deep learning
This work overviews recent research results that show how tools from deep learning are shaping up to become a powerful tool for the automated design of near-optimal auctions auctions and recovers to a high degree of accuracy essentially all known analytically derived solutions for multi-item settings.
An MDP-Based Approach to Online Mechanism Design
This work considers the problem of maximizing the total long-term value of the system despite the self-interest of agents, and induces a Markov Decision Process (MDP), which when solved can be used to implement optimal policies in a truth-revealing Bayesian-Nash equilibrium.
Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges
Experimental and theoretical analysis suggest a simple Threshold scheme, which gives surplus to agents with payments further than a certain threshold value from their Vickrey payments, which appears able to exploit agent uncertainty about bids from other agents to reduce manipulation and boost allocative efficiency in comparison with other simple rules.
Informed Truthfulness in Multi-Task Peer Prediction
The Correlated Agreement (CA) mechanism is introduced, which handles multiple signals and provides informed truthfulness: no strategy profile provides more payoff in equilibrium than truthful reporting, and the truthful equilibrium is strictly better than any uninformed strategy.
Pricing WiFi at Starbucks: issues in online mechanism design
It is shown how the standard results of mechanism design can be modified to apply to this setting, provide conditions under which efficient and incentive compatible mechanisms exist and analyze several important online models including wireless networks and web serving.
Truth, justice, and cake cutting
Computational-Mechanism Design: A Call to Arms
This work states that game theory has developed powerful tools for analyzing, predicting, and controlling the behavior of self-interested agents and decision making in systems with multiple autonomous actors provide a foundation for building multiagent software systems.