English
Related papers

Related papers: The Peter Principle Revisited: A Computational Stu…

200 papers

In the future, artificial learning agents are likely to become increasingly widespread in our society. They will interact with both other learning agents and humans in a variety of complex settings including social dilemmas. We consider the…

Computer Science and Game Theory · Computer Science 2019-11-21 Tobias Baumann , Thore Graepel , John Shawe-Taylor

Systems engineering processes coordinate the effort of different individuals to generate a product satisfying certain requirements. As the involved engineers are self-interested agents, the goals at different levels of the systems…

Multiagent Systems · Computer Science 2023-07-19 Salar Safarkhani , Ilias Bilionis , Jitesh Panchal

Agent-based models describing social interactions among individuals can help to better understand emerging macroscopic patterns in societies. One of the topics which is worth tackling is the formation of different kinds of hierarchies that…

Physics and Society · Physics 2025-01-28 Marc Sadurní , Josep Perelló , Miquel Montero

Peters (2011a) defined an optimal leverage which maximizes the time-average growth rate of an investment held at constant leverage. It was hypothesized that this optimal leverage is attracted to 1, such that, e.g., leveraging an investment…

General Finance · Quantitative Finance 2020-06-12 Ole Peters , Alexander Adamou

A standard belief on emerging collective behavior is that it emerges from simple individual rules. Most of the mathematical research on such collective behavior starts from imperative individual rules, like always go to the center. But how…

Populations and Evolution · Quantitative Biology 2018-02-23 El Mahdi El Mhamdi , Rachid Guerraoui , Alexandre Maurer , Vladislav Tempez

Patterns of wins and losses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one…

Physics and Society · Physics 2025-11-03 Maximilian Jerdee , M. E. J. Newman

Reinforcement learning is a machine learning approach based on behavioral psychology. It is focused on learning agents that can acquire knowledge and learn to carry out new tasks by interacting with the environment. However, a problem…

Artificial Intelligence · Computer Science 2022-12-15 Hugo Muñoz , Ernesto Portugal , Angel Ayala , Bruno Fernandes , Francisco Cruz

In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning (RL) in competition tasks. Within the actor-critic RL, we introduce multiple…

Machine Learning · Computer Science 2020-03-03 Zehong Cao , Chin-Teng Lin

We propose a novel model to explain the mechanisms underlying dominance hierarchical structures. Guided by a predetermined social convention, agents with limited cognitive abilities optimize their strategies in a Hawk-Dove game. We find…

Populations and Evolution · Quantitative Biology 2022-06-22 Hanyuan Huang , Jiabin Wu

We propose a novel network formation game that explains the emergence of various hierarchical structures in groups where self-interested or utility-maximizing individuals decide to establish or severe relationships of authority or…

Computer Science and Game Theory · Computer Science 2021-09-15 Pedro Cisneros-Velarde , Francesco Bullo

Ranking athletes by their performance in competitions and tournaments is common in every popular sport and has significant benefits that contribute to both the organization and strategic aspects of competitions. Although rankings are…

Physics and Society · Physics 2025-08-28 Bogdán Asztalos , Boldizsár Balázs , Gergely Palla , Tamás Vicsek

Human behavioural patterns exhibit selfish or competitive, as well as selfless or altruistic tendencies, both of which have demonstrable effects on human social and economic activity. In behavioural economics, such effects have…

Multiagent Systems · Computer Science 2021-04-28 Jan E. Snellman , Gerardo Iñiguez , János Kertész , R. A. Barrio , Kimmo K. Kaski

We study individual decision-making behavioral on generic view. Using a formal mathematical model, we investigate the action mechanism of decision behavioral under subjective perception changing of task attributes. Our model is built on…

General Economics · Economics 2018-09-14 Xingguang Chen

Information sharing between individuals is crucial to improve performance in collective tasks. However, in a competitive world, individuals may be reluctant to share information with the others, and it is still unclear how the presence of…

Physics and Society · Physics 2026-05-04 Ye Wang , Andrea Civilini , Anzhi Sheng , Xiaojie Chen , Long Wang , Vito Latora

We investigate a novel approach to resilient distributed optimization with quadratic costs in a multi-agent system prone to unexpected events that make some agents misbehave. In contrast to commonly adopted filtering strategies, we draw…

Systems and Control · Electrical Eng. & Systems 2025-02-11 Luca Ballotta , Giacomo Como , Jeff S. Shamma , Luca Schenato

Many real-world human behaviors can be characterized as a sequential decision making processes, such as urban travelers choices of transport modes and routes (Wu et al. 2017). Differing from choices controlled by machines, which in general…

Artificial Intelligence · Computer Science 2019-07-12 Guojun Wu , Yanhua Li , Zhenming Liu , Jie Bao , Yu Zheng , Jieping Ye , Jun Luo

The hidden-action model provides an optimal sharing rule for situations in which a principal assigns a task to an agent who makes an effort to carry out the task assigned to him. However, the principal can only observe the task outcome but…

General Economics · Economics 2022-10-18 Stephan Leitner , Friederike Wall

We study a social network consisting of agents organized as a hierarchical M-ary rooted tree, common in enterprise and military organizational structures. The goal is to aggregate information to solve a binary hypothesis testing problem.…

Social and Information Networks · Computer Science 2015-06-05 Zhenliang Zhang , Edwin K. P. Chong , Ali Pezeshki , William Moran , Stephen D. Howard

Incentives are more likely to elicit desired outcomes when they are designed based on accurate models of agents' strategic behavior. A growing literature, however, suggests that people do not quite behave like standard economic agents in a…

Computer Science and Game Theory · Computer Science 2014-06-09 Arpita Ghosh , Robert Kleinberg

Modern recommendation systems rely on the wisdom of the crowd to learn the optimal course of action. This induces an inherent mis-alignment of incentives between the system's objective to learn (explore) and the individual users' objective…

Computer Science and Game Theory · Computer Science 2018-07-06 Gal Bahar , Rann Smorodinsky , Moshe Tennenholtz