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It is a common practice in the current literature of electricity markets to use game-theoretic approaches for strategic price bidding. However, they generally rely on the assumption that the strategic bidders have prior knowledge of rival…

Computer Science and Game Theory · Computer Science 2024-04-05 Arega Getaneh Abate , Dorsa Majdi , Jalal Kazempour , Maryam Kamgarpour

During the first step of practical reasoning, i.e. deliberation or goals selection, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. Explainable Artificial Intelligence (XAI)…

Artificial Intelligence · Computer Science 2020-09-15 Mariela Morveli-Espinoza , Cesar Augusto Tacla , Henrique Jasinski

We study whether large language models acting as autonomous bidders can tacitly collude by coordinating when to accept platform posted payouts in repeated Dutch auctions, without any communication. We present a minimal repeated auction…

Computer Science and Game Theory · Computer Science 2025-12-01 Sriram Tolety

In this work, we consider the problem of searching people in an unconstrained environment, with natural language descriptions. Specifically, we study how to systematically design an algorithm to effectively acquire descriptions from humans.…

Robotics · Computer Science 2020-02-21 Vikram Shree , Wei-Lun Chao , Mark Campbell

Bargaining can be used to resolve mixed-motive games in multi-agent systems. Although there is an abundance of negotiation strategies implemented in automated negotiating agents, most agents are based on single fixed strategies, while it is…

Multiagent Systems · Computer Science 2022-12-21 Bram M. Renting , Holger H. Hoos , Catholijn M. Jonker

Graph games of infinite length are a natural model for open reactive processes: one player represents the controller, trying to ensure a given specification, and the other represents a hostile environment. The evolution of the system…

Computer Science and Game Theory · Computer Science 2010-06-09 Julien Cristau , Claire David , Florian Horn

Advertising becomes one of the most popular ways of monetizing an online transaction platform. Usually, sponsored advertisements are posted on the most attractive positions to enhance the number of clicks. However, multiple e-commerce…

Computer Science and Game Theory · Computer Science 2022-04-22 Weian Li , Qi Qi , Changjun Wang , Changyuan Yu

This survey examines the most effective retrieval algorithms utilized in ad recommendation and content recommendation systems. Ad targeting algorithms rely on detailed user profiles and behavioral data to deliver personalized…

Information Retrieval · Computer Science 2024-07-22 Yu Zhao , Fang Liu

In a sponsored search auction, decisions about how to rank ads impose tradeoffs between objectives such as revenue and welfare. In this paper, we examine how these tradeoffs should be made. We begin by arguing that the most natural solution…

Computer Science and Game Theory · Computer Science 2013-04-30 Ben Roberts , Dinan Gunawardena , Ian A. Kash , Peter Key

In the context of strategic games, we provide an axiomatic proof of the statement Common knowledge of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies.…

Computer Science and Game Theory · Computer Science 2010-06-28 Jonathan A. Zvesper , Krzysztof R. Apt

We consider an online ad network problem in which an ad exchange auctions ad slots and intermediaries called demand side platforms (DSPs) buy these ad slots for their clients (advertisers). An intermediary represents multiple advertisers.…

Computer Science and Game Theory · Computer Science 2019-10-07 Rahul Meshram , Kesav Kaza

The commercialization of LLM applications is the next frontier in online advertising, with LLM-native advertising emerging as a promising paradigm by integrating ads into LLM-generated content. However, classic mechanisms are no longer…

Computer Science and Game Theory · Computer Science 2026-04-28 Chujie Zhao , Qun Hu , Shiping Song , Dagui Chen , Han Zhu , Jian Xu , Bo Zheng

We model a competitive market where AI agents buy answers from upstream generative models and resell them to users who differ in how much they value accuracy and in how much they fear hallucinations. Agents can privately exert effort for…

Theoretical Economics · Economics 2026-04-14 Engin Iyidogan , Ali I. Ozkes

We initiate the study of markets for private data, though the lens of differential privacy. Although the purchase and sale of private data has already begun on a large scale, a theory of privacy as a commodity is missing. In this paper, we…

Computer Science and Game Theory · Computer Science 2011-11-30 Arpita Ghosh , Aaron Roth

Negotiation is a complex activity involving strategic reasoning, persuasion, and psychology. An average person is often far from an expert in negotiation. Our goal is to assist humans to become better negotiators through a…

Computation and Language · Computer Science 2019-10-01 Yiheng Zhou , He He , Alan W Black , Yulia Tsvetkov

In modern advertising platforms, learning algorithms are deployed by budget-constrained bidders to maximize their accumulated value. These algorithms often offer classical utility guarantees like no-regret, i.e., the agent's utility is at…

Computer Science and Game Theory · Computer Science 2026-02-23 Giannis Fikioris , Robert Kleinberg , Yoav Kolumbus , Yishay Mansour , Eva Tardos

Our aim is to design mechanisms that motivate all agents to reveal their predictions truthfully and promptly. For myopic agents, proper scoring rules induce truthfulness. However, as has been described in the literature, when agents take…

Computer Science and Game Theory · Computer Science 2019-12-05 Amir Ban

In lowest unique bid auctions, $N$ players bid for an item. The winner is whoever places the \emph{lowest} bid, provided that it is also unique. We use a grand canonical approach to derive an analytical expression for the equilibrium…

Computer Science and Game Theory · Computer Science 2015-05-28 Simone Pigolotti , Sebastian Bernhardsson , Jeppe Juul , Gorm Galster , Pierpaolo Vivo

In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that…

Machine Learning · Statistics 2025-02-14 Matilde Tullii , Solenne Gaucher , Nadav Merlis , Vianney Perchet

Artificial Intelligence (AI) is being increasingly used to develop systems that produce intelligent solutions. However, there is a major concern that whether the systems built will be trusted by humans. In order to establish trust in AI…

Artificial Intelligence · Computer Science 2020-05-13 Quratul-ain Mahesar , Simon Parsons