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A service robot can provide a smoother interaction experience if it has the ability to proactively detect whether a nearby user intends to interact, in order to adapt its behavior e.g. by explicitly showing that it is available to provide a…

Robotics · Computer Science 2024-10-07 Gabriele Abbate , Alessandro Giusti , Viktor Schmuck , Oya Celiktutan , Antonio Paolillo

This paper addresses the problem of online learning in a dynamic setting. We consider a social network in which each individual observes a private signal about the underlying state of the world and communicates with her neighbors at each…

Optimization and Control · Mathematics 2013-10-02 Shahin Shahrampour , Alexander Rakhlin , Ali Jadbabaie

Simulating trajectories of virtual crowds is a commonly encountered task in Computer Graphics. Several recent works have applied Reinforcement Learning methods to animate virtual agents, however they often make different design choices when…

Machine Learning · Computer Science 2022-09-21 Ariel Kwiatkowski , Vicky Kalogeiton , Julien Pettré , Marie-Paule Cani

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature…

Machine Learning · Statistics 2024-06-27 Pangpang Liu , Zhuoran Yang , Zhaoran Wang , Will Wei Sun

A seller offers a buyer a schedule of transfers and associated product qualities. After observing this schedule, the buyer chooses a flexible costly signal about his type. We show it is without loss to focus on a class of mechanisms that…

Theoretical Economics · Economics 2025-02-20 Jeffrey Mensch , Doron Ravid

We propose a new online learning model for learning with preference feedback. The model is especially suited for applications like web search and recommender systems, where preference data is readily available from implicit user feedback…

Machine Learning · Computer Science 2011-11-04 Pannagadatta K. Shivaswamy , Thorsten Joachims

In social learning environments, agents acquire information from both private signals and the observed actions of predecessors, referred to as history. We define the value of history as the gain in expected payoff from accessing both the…

Theoretical Economics · Economics 2025-07-16 Hiroto Sato , Konan Shimizu

When a business sells to another business (B2B), the buying business is represented by a group of individuals, termed account, who collectively decide whether to buy. The seller advertises to each individual and interacts with them, mostly…

Machine Learning · Computer Science 2022-09-29 Atanu R. Sinha , Gautam Choudhary , Mansi Agarwal , Shivansh Bindal , Abhishek Pande , Camille Girabawe

A fundamental decision faced by a firm hiring employees - and a familiar one to anyone who has dealt with the academic job market, for example - is deciding what caliber of candidates to pursue. Should the firm try to increase its…

Computer Science and Game Theory · Computer Science 2014-12-08 Jon Kleinberg , Sigal Oren

We propose a simple model to explore an educational phenomenon where the correct answer emerges from group discussion. We construct our model based on several plausible assumptions: (i) We tend to follow peers' opinions. However, if a…

Physics and Society · Physics 2025-05-27 Jibeom Seo , Beom Jun Kim

Reputation and punishment are significant guidelines for regulating individual behavior in human society, and those with a good reputation are more likely to be imitated by others. In addition, society imposes varying degrees of punishment…

Social and Information Networks · Computer Science 2025-11-25 Gui Zhang , Yichao Yao , Ziyan Zeng , Minyu Feng , Manuel Chica

User-generated reviews serve as crucial references in shopper's decision-making process. Moreover, they improve product sales and validate the reputation of the website as a whole. Thus, it becomes important to design reviews ranking…

Information Retrieval · Computer Science 2020-09-08 Akhil Sai Peddireddy

Imitation learning seeks to learn an expert policy from sampled demonstrations. However, in the real world, it is often difficult to find a perfect expert and avoiding dangerous behaviors becomes relevant for safety reasons. We present the…

Machine Learning · Computer Science 2019-09-26 David Venuto , Leonard Boussioux , Junhao Wang , Rola Dali , Jhelum Chakravorty , Yoshua Bengio , Doina Precup

An ability to predict the popularity dynamics of individual items within a complex evolving system has important implications in a wide range of domains. Here we propose a deep learning attention mechanism to model the process through which…

Social and Information Networks · Computer Science 2022-04-22 Sha Yuan , Yu Zhang , Jie Tang , Huawei Shen , Xingxing Wei

Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that…

The bystander effect is a social psychological phenomenon in which individuals are less likely to help a person potentially in need if there are others present. Sociologists and psychologists have proposed multiple plausible reasons for the…

Physics and Society · Physics 2026-01-13 Tiffanie Ng , Sara M Clifton

Indirect reciprocity is a reputation-based mechanism for cooperation in social dilemma situations when individuals do not repeatedly meet. The conditions under which cooperation based on indirect reciprocity occurs have been examined in…

Populations and Evolution · Quantitative Biology 2012-11-22 Shoma Tanabe , Hideyuki Suzuki , Naoki Masuda

Before purchase, a buyer of an experience good learns about the product's fit using various information sources, including some of which the seller may be unaware of. The buyer, however, can conclusively learn the fit only after purchasing…

Computer Science and Game Theory · Computer Science 2020-05-21 Toomas Hinnosaar , Keiichi Kawai

In this paper, we study the problem of deceptive reinforcement learning to preserve the privacy of a reward function. Reinforcement learning is the problem of finding a behaviour policy based on rewards received from exploratory behaviour.…

Machine Learning · Computer Science 2021-02-08 Zhengshang Liu , Yue Yang , Tim Miller , Peta Masters

Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing…

Neurons and Cognition · Quantitative Biology 2023-05-15 Max Taylor-Davies , Stephanie Droop , Christopher G. Lucas