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In decision-making, individuals often rely on intuition, which can occasionally yield suboptimal outcomes. This study examines the impact of intuitive decision-making on individuals who are confronted with limited position information in…

Physics and Society · Physics 2024-05-07 Fanyuan Meng , Hui Xiao , Xinlin Wu , Xiaojun Hu , Xiaojie Niu , Sheng Chen , Yu Liu

"Value alignment" (VA) is considered as one of the top priorities in AI research. Much of the existing research focuses on the "A" part and not the "V" part of "value alignment." This paper corrects that neglect by emphasizing the "value"…

Artificial Intelligence · Computer Science 2018-10-29 Tae Wan Kim , Thomas Donaldson , John Hooker

We consider the problem of how strategic users with asymmetric information can learn an underlying time varying state in a user-recommendation system. Users who observe private signals about the state, sequentially make a decision about…

Computer Science and Game Theory · Computer Science 2018-04-17 Deepanshu Vasal , Vijay Subramanian , Achilleas Anastasopoulos

We investigate a variation of the classical voter model in which the set of influencing agents depends on an individual's current opinion. The initial population consists of a random sample of equally sized sub-populations for each state,…

Physics and Society · Physics 2025-09-30 Francisco J. Muñoz , Juan Carlos Nuño

The use of natural language and voice-based interfaces gradu-ally transforms how consumers search, shop, and express their preferences. The current work explores how changes in the syntactical structure of the interaction with…

Artificial Intelligence · Computer Science 2021-11-04 Christian Hildebrand , Donna Hoffman , Tom Novak

In value-based reinforcement learning (RL), unlike in supervised learning, the agent faces not a single, stationary, approximation problem, but a sequence of value prediction problems. Each time the policy improves, the nature of the…

Machine Learning · Computer Science 2021-01-05 Will Dabney , André Barreto , Mark Rowland , Robert Dadashi , John Quan , Marc G. Bellemare , David Silver

Consumers are increasingly delegating purchase decisions to AI agents, providing natural-language descriptions of their preferences and identity. We argue that these representations constitute an information channel, role coherence, through…

Multiagent Systems · Computer Science 2026-04-30 Soogand Alavi , Salar Nozari

In general, self help systems are being increasingly deployed by service based industries because they are capable of delivering better customer service and increasingly the switch is to voice based self help systems because they provide a…

Computation and Language · Computer Science 2015-04-08 Sunil Kumar Kopparapu

Lately, personalized marketing has become important for retail/e-retail firms due to significant rise in online shopping and market competition. Increase in online shopping and high market competition has led to an increase in promotional…

Machine Learning · Computer Science 2020-10-19 Ankur Verma

With the recent advancements in Artificial Intelligence (AI), Intelligent Virtual Assistants (IVA) such as Alexa, Google Home, etc., have become a ubiquitous part of many homes. Currently, such IVAs are mostly audio-based, but going…

Multimedia · Computer Science 2019-12-27 Shachi H Kumar , Eda Okur , Saurav Sahay , Jonathan Huang , Lama Nachman

We study a single-buyer pricing problem with unreliable side information, motivated by the increasing use of AI-assisted decision-making and LLM-based predictions. The seller observes a private sample that may be either accurate (coinciding…

Computer Science and Game Theory · Computer Science 2026-04-06 Zhihao Gavin Tang , Yixin Tao , Shixin Wang

In this paper, we consider the revealed preferences problem from a learning perspective. Every day, a price vector and a budget is drawn from an unknown distribution, and a rational agent buys his most preferred bundle according to some…

Computer Science and Game Theory · Computer Science 2012-11-20 Morteza Zadimoghaddam , Aaron Roth

Variances in ad impression outcomes across demographic groups are increasingly considered to be potentially indicative of algorithmic bias in personalized ads systems. While there are many definitions of fairness that could be applicable in…

Recent years have witnessed remarkable progress in 3D content generation. However, corresponding evaluation methods struggle to keep pace. Automatic approaches have proven challenging to align with human preferences, and the mixed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Weitao Wang , Haoran Xu , Yuxiao Yang , Zhifang Liu , Jun Meng , Haoqian Wang

We study the mechanism design problem of selling $k$ items to unit-demand buyers with private valuations for the items. A buyer either participates directly in the auction or is represented by an intermediary, who represents a subset of…

Computer Science and Game Theory · Computer Science 2021-11-23 Gagan Aggarwal , Kshipra Bhawalkar , Guru Guruganesh , Andres Perlroth

Persuasion is a key aspect of what it means to be human, and is central to business, politics, and other endeavors. Advancements in artificial intelligence (AI) have produced AI systems that are capable of persuading humans to buy products,…

Computers and Society · Computer Science 2023-03-16 Matthew Burtell , Thomas Woodside

One of the impediments to the efficiency of information markets is the inherent information asymmetry present in them, exacerbated by the "buyer's inspection paradox" (the buyer cannot mitigate the asymmetry by "inspecting" the information,…

Computer Science and Game Theory · Computer Science 2026-04-13 Abhimanyu Pallavi Sudhir , Long Tran-Thanh

We study the asymptotic average-case efficiency of static and anonymous posted prices for $n$ agents and $m(n)$ multiple identical items with $m(n)=o\left(\frac{n}{\log n}\right)$. When valuations are drawn i.i.d from some fixed continuous…

Computer Science and Game Theory · Computer Science 2019-01-09 Urban Larsson , Ron Lavi

Recent advances in natural language processing and deep learning have accelerated the development of digital assistants. In conversational commerce, these assistants help customers find suitable products in online shops through natural…

Human-Computer Interaction · Computer Science 2024-10-03 Kevin Schott , Andrea Papenmeier , Daniel Hienert , Dagmar Kern

Auction-based recommender systems are prevalent in online advertising platforms, but they are typically optimized to allocate recommendation slots based on immediate expected return metrics, neglecting the downstream effects of…

Information Retrieval · Computer Science 2023-08-01 Ruiyang Xu , Jalaj Bhandari , Dmytro Korenkevych , Fan Liu , Yuchen He , Alex Nikulkov , Zheqing Zhu