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Found 10 papers, 1 papers with code
Global Decision-Making via Local Economic Transactions
This paper seeks to establish a mechanism for directing a collection of simple, specialized, self-interested agents to solve what traditionally are posed as monolithic single-agent sequential decision problems with a central global objective.
Contracting with a Learning Agent
We initiate the study of repeated contracts with a learning agent, focusing on agents who achieve no-regret outcomes.
Prior-free Dynamic Mechanism Design With Limited Liability
We show that under these constraints, the auctioneer can attain a constant fraction of the "sell the business" benchmark, but no more than $2/e$ of this benchmark.
Computer Science and Game Theory Theoretical Economics
Optimal Multi-Dimensional Mechanisms are not Locally-Implementable
We show that this phenomenon already occurs with just two bidders, even when one bidder is single-dimensional, and when the other bidder is barely multi-dimensional.
Computer Science and Game Theory
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
This paper seeks to establish a framework for directing a society of simple, specialized, self-interested agents to solve what traditionally are posed as monolithic single-agent sequential decision problems.
Auction learning as a two-player game
This not only circumvents the need for an expensive hyper-parameter search (as in prior work), but also provides a principled metric to compare the performance of two auctions (absent from prior work).
A Permutation-Equivariant Neural Network Architecture For Auction Design
Designing an incentive compatible auction that maximizes expected revenue is a central problem in Auction Design.
The Sample Complexity of Up-to-$\varepsilon$ Multi-Dimensional Revenue Maximization
We consider the sample complexity of revenue maximization for multiple bidders in unrestricted multi-dimensional settings.
Selling to a No-Regret Buyer
- There exists a learning algorithm $\mathcal{A}$ such that if the buyer bids according to $\mathcal{A}$ then the optimal strategy for the seller is simply to post the Myerson reserve for $D$ every round.
Multi-armed Bandit Problems with Strategic Arms
We study a strategic version of the multi-armed bandit problem, where each arm is an individual strategic agent and we, the principal, pull one arm each round.
