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Two issues of algorithmic collusion are addressed in this paper. First, we show that in a general class of symmetric games, including Prisoner's Dilemma, Bertrand competition, and any (nonlinear) mixture of first and second price auction,…

Theoretical Economics · Economics 2024-09-05 Zhang Xu , Wei Zhao

Precise day-ahead forecasts for electricity prices are crucial to ensure efficient portfolio management, support strategic decision-making for power plant operations, enable efficient battery storage optimization, and facilitate demand…

Machine Learning · Computer Science 2026-03-31 Btissame El Mahtout , Florian Ziel

We cast the problem of combinatorial auction design in a Bayesian framework in order to incorporate prior information into the auction process and minimize the number of rounds to convergence. We first develop a generative model of agent…

Computer Science and Game Theory · Computer Science 2018-11-19 Gianluca Brero , Sébastien Lahaie

Collusion in market pricing is a concept associated with human actions to raise market prices through artificially limited supply. Recently, the idea of algorithmic collusion was put forward, where the human action in the pricing process is…

Theoretical Economics · Economics 2025-01-29 Suzie Grondin , Arthur Charpentier , Philipp Ratz

In settings where full incentive-compatibility is not available, such as core-constraint combinatorial auctions and budget-balanced combinatorial exchanges, we may wish to design mechanisms that are as incentive-compatible as possible. This…

Computer Science and Game Theory · Computer Science 2015-03-24 Benjamin Lubin

Priced timed automata provide a natural model for quantitative analysis of real-time systems and have been successfully applied in various scheduling and planning problems. The optimal reachability problem for linearly-priced timed automata…

Formal Languages and Automata Theory · Computer Science 2016-12-16 Devendra Bhave , Shankara Narayanan Krishna , Ashutosh Trivedi

In the contextual pricing problem a seller repeatedly obtains products described by an adversarially chosen feature vector in $\mathbb{R}^d$ and only observes the purchasing decisions of a buyer with a fixed but unknown linear valuation…

Data Structures and Algorithms · Computer Science 2021-02-25 Allen Liu , Renato Paes Leme , Jon Schneider

A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) in which the constraint matrix is revealed column by column along with the corresponding…

Data Structures and Algorithms · Computer Science 2014-04-10 Shipra Agrawal , Zizhuo Wang , Yinyu Ye

Price differentiation is a common strategy in many markets. In this paper, we study a static multiproduct price optimization problem with demand given by a discrete mixed multinomial logit model. By considering a mixed logit model that…

Optimization and Control · Mathematics 2023-04-05 Ahmadreza Marandi , Virginie Lurkin

We present a method for finding envy-free prices in a combinatorial auction where the consumers' number $n$ coincides with that of distinct items for sale, each consumer can buy one single item and each item has only one unit available.…

Computer Science and Game Theory · Computer Science 2023-08-25 Marcos Salvatierra , Juan G. Colonna , Mario Salvatierra , Alcides de C. Amorim Neto

A patient seller aims to sell a good to an impatient buyer (i.e., one who discounts utility over time). The buyer will remain in the market for a period of time $T$, and her private value is drawn from a publicly known distribution. What is…

Computer Science and Game Theory · Computer Science 2023-02-14 Yuan Deng , Jieming Mao , Balasubramanian Sivan , Kangning Wang

In this article we consider combinatorial markets with valuations only for singletons and pairs of buy/sell-orders for swapping two items in equal quantity. We provide an algorithm that permits polynomial time market-clearing and -pricing.…

Optimization and Control · Mathematics 2017-10-30 Johannes C. Müller , Sebastian Pokutta , Alexander Martin , Susanne Pape , Andrea Peter , Thomas Winter

Algorithmic pricing raises a question of interpretation as well as intervention: when autonomous deep-learning pricing systems sustain supracompetitive prices, what strategic pattern have they learned, and how might market institutions…

Theoretical Economics · Economics 2026-05-19 Soumen Banerjee

In this paper we propose models of combinatorial algorithms for the Boolean Matrix Multiplication (BMM), and prove lower bounds on computing BMM in these models. First, we give a relatively relaxed combinatorial model which is an extension…

Computational Complexity · Computer Science 2018-01-17 Debarati Das , Michal Koucký , Michael Saks

To overcome the #P-hardness of computing/updating prices in logarithm market scoring rule-based (LMSR-based) combinatorial prediction markets, Chen et al. [5] recently used a simple Bayesian network to represent the prices of securities in…

Computer Science and Game Theory · Computer Science 2012-02-20 David M. Pennock , Lirong Xia

The emerging edge computing paradigm promises to deliver superior user experience and enable a wide range of Internet of Things (IoT) applications. In this work, we propose a new market-based framework for efficiently allocating resources…

Computer Science and Game Theory · Computer Science 2018-05-09 Duong Tung Nguyen , Long Bao Le , Vijay Bhargava

We present an algorithm for computing pure-strategy epsilon-perfect Bayesian equilibria in sequential auctions with continuous action and value spaces. Importantly, our algorithm includes a verification phase that computes an upper bound on…

Computer Science and Game Theory · Computer Science 2025-02-19 Vinzenz Thoma , Vitor Bosshard , Sven Seuken

Identical products being sold at different prices in different locations is a common phenomenon. Price differences might occur due to various reasons such as shipping costs, trade restrictions and price discrimination. To model such…

Computer Science and Game Theory · Computer Science 2010-08-02 Sourav Chakraborty , Nikhil Devanur , Chinmay Karande

We study revenue optimization learning algorithms for posted-price auctions with strategic buyers. We analyze a very broad family of monotone regret minimization algorithms for this problem, which includes the previously best known…

Machine Learning · Computer Science 2014-11-25 Mehryar Mohri , Andres Muñoz Medina

We revisit the fundamental Boolean Matrix Multiplication (BMM) problem. With the invention of algebraic fast matrix multiplication over 50 years ago, it also became known that BMM can be solved in truly subcubic $O(n^\omega)$ time, where…

Data Structures and Algorithms · Computer Science 2024-05-28 Amir Abboud , Nick Fischer , Zander Kelley , Shachar Lovett , Raghu Meka