Pareto Efficient Auctions with Interest Rates

Authors: Gagan Goel, Vahab Mirrokni, Renato Paes Leme1989-1995

AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our main result is an incentive compatible and Pareto-efficient auction for a divisible multi-unit setting with 2 players who are able to borrow money with the same interest rate. The auction is an ascending price clock auction that bears some similarities to the clinching auction but at the same time is a considerable departure from this framework: allocated goods can be de-allocated in future and given to other agents and prices for previously allocated goods can be raised.
Researcher Affiliation Industry Gagan Goel, Vahab Mirrokni, Renato Paes Leme Google Research gagangoel@gmail.com, mirrokni@google.com, renatoppl@google.com
Pseudocode Yes Taxed Ascending Auction Initialize dxi[p] = 0 and pri[p] = p for all prices p, p1 = p2 = 0 and i = 1. Main Loop: Repeat while p1 v1 or p2 v2. 1. Choose agent in round-robin schedule and increase price: i = 3 i, pi = pi + ϵ. 2. Update price for previously allocated goods: if p i < v i, then for all prices p γ 1pi, update pri[p ] = γ 1pi. 3. Recollections: if γ 1p > vi, collect back all the goods allocated to player i and add them to the pool. Formally: x = x + P q xi[q] and xi[q] = 0 for all q. if i total payment is larger then Bi, collect back the most expensive goods and add them to the -pool. Formally: if πi > Bi, find p such that P q<p pri[q] dxi[q] Bi and P q p pri[q] dxi[q] > Bi. Let Ki = 1 pri[p ][Bi P q<p pri[q] dxi[q]] be the amount of goods at price p the player can keep. And update: x = x + (xi[p ] Ki) + P q>p dxi[q], dxi[q] = 0 for q > p and dxi[p ] = Ki. 4. Clinching: The demand of i decreases to di = 1 pi [Bi πi] if pi vi and di = 0 otherwise; and compute the clinched amount for player i as δ i = [1 x1 x2 x di]+ and allocate: dx i[p i] = dx i[p i] + δ i. 5. Pool Re-assignment: if p i > v i, then dxi[pi] = dxi[pi] + x , x = 0.
Open Source Code No The paper describes a theoretical auction mechanism and provides proofs, but it does not provide any statement or link for open-source code specific to its implementation.
Open Datasets No This paper focuses on theoretical contributions and does not involve the use of datasets for training.
Dataset Splits No This paper focuses on theoretical contributions and does not involve the use of validation sets.
Hardware Specification No This paper focuses on theoretical contributions and does not describe any experimental setup involving specific hardware.
Software Dependencies No This paper focuses on theoretical contributions and does not specify any software dependencies for experimental replication.
Experiment Setup No This paper focuses on theoretical contributions and does not provide details about an experimental setup, such as hyperparameters or system-level training settings.