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We use methods from network science to analyze corruption risk in a large administrative dataset of over 4 million public procurement contracts from European Union member states covering the years 2008-2016. By mapping procurement markets…

General Finance · Quantitative Finance 2019-09-20 Johannes Wachs , Mihály Fazekas , János Kertész

We study the interpersonal trust of a population of agents, asking whether chance may decide if a population ends up in a high trust or low trust state. We model this by a discrete time, random matching stochastic coordination game. Agents…

Physics and Society · Physics 2024-05-20 Benedikt V. Meylahn , Arnoud V. den Boer , Michel Mandjes

We introduce a method to infer lead-lag networks of agents' actions in complex systems. These networks open the way to both microscopic and macroscopic states prediction in such systems. We apply this method to trader-resolved data in the…

Trading and Market Microstructure · Quantitative Finance 2018-07-27 Damien Challet , Rémy Chicheportiche , Mehdi Lallouache , Serge Kassibrakis

In recent years, there has been a proliferation of online gambling sites, which made gambling more accessible with a consequent rise in related problems, such as addiction. Hence, the analysis of the gambling behaviour at both the…

Physics and Society · Physics 2019-07-24 Giuseppe Toscani , Andrea Tosin , Mattia Zanella

Synthetic corruptions gathered into a benchmark are frequently used to measure neural network robustness to distribution shifts. However, robustness to synthetic corruption benchmarks is not always predictive of robustness to distribution…

Computer Vision and Pattern Recognition · Computer Science 2021-11-19 Alfred Laugros , Alice Caplier , Matthieu Ospici

Following a long tradition of physicists who have noticed that the Ising model provides a general background to build realistic models of social interactions, we study a model of financial price dynamics resulting from the collective…

Statistical Mechanics · Physics 2008-12-02 Didier Sornette , Wei-Xing Zhou

This paper proposes models of learning process in teams of individuals who collectively execute a sequence of tasks and whose actions are determined by individual skill levels and networks of interpersonal appraisals and influence. The…

Social and Information Networks · Computer Science 2016-10-03 Wenjun Mei , Noah E. Friedkin , Kyle Lewis , Francesco Bullo

The heterogeneity of the influence processes is an important feature of social systems: how we perceive social influence and how we influence other individuals is heavily influenced by our opinion and non-opinion attributes. The latter…

Social and Information Networks · Computer Science 2022-09-07 Ivan V. Kozitsin

Modern AI systems increasingly operate inside markets and institutions where data, behavior, and incentives are endogenous. This paper develops an economic foundation for multi-agent learning by studying a principal-agent interaction in a…

Machine Learning · Statistics 2026-01-08 Nassim Helou

We analyze income tax evasion dynamics in a standard model of statistical mechanics, the Ising model of ferromagnetism. However, in contrast to previous research, we use an inhomogeneous multi-dimensional Ising model where the local degrees…

Physics and Society · Physics 2011-12-02 Michael Pickhardt , Goetz Seibold

This paper investigates causal influences between agents linked by a social graph and interacting over time. In particular, the work examines the dynamics of social learning models and distributed decision-making protocols, and derives…

Social and Information Networks · Computer Science 2026-05-19 Mert Kayaalp , Ali H. Sayed

Magnetic fluids are colloidal suspensions of ferromagnetic particles covered with a surfactant layer, dispersed in a host liquid. The existence of cooperative phenomena in such magnetic colloidal systems, makes the determining of their…

Materials Science · Physics 2007-05-23 D. Andru Vangheli , H. Covlescu , Gh. Ardelean , C. Stelia

Text classification models, especially neural networks based models, have reached very high accuracy on many popular benchmark datasets. Yet, such models when deployed in real world applications, tend to perform badly. The primary reason is…

Computation and Language · Computer Science 2020-02-04 Utkarsh Desai , Srikanth Tamilselvam , Jassimran Kaur , Senthil Mani , Shreya Khare

This article proposes a fundamental methodological shift in the modelling of policy interventions for sustainability transitions in order to account for complexity (e.g. self-reinforcing mechanism arising from multi-agent interactions) and…

Physics and Society · Physics 2016-03-23 J. -F. Mercure , H. Pollitt , A. M. Bassi , J. E Viñuales , N. R. Edwards

We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We…

Trading and Market Microstructure · Quantitative Finance 2015-06-04 Ribin Lye , James Peng Lung Tan , Siew Ann Cheong

Information is often stored in a distributed and proprietary form, and agents who own information are often self-interested and require incentives to reveal their information. Suitable mechanisms are required to elicit and aggregate such…

Multiagent Systems · Computer Science 2022-12-02 Wenlong Wang , Thomas Pfeiffer

Occupation probabilities for primary-secondary-primary cell strings and correlation functions for primary sites of a decorated lattice model are expressed through the well-studied partition function and correlation functions of the Ising…

Statistical Mechanics · Physics 2009-10-31 I. Ispolatov , K. Koga , B. Widom

'Rich get richer' rule comforts previously often chosen actions. What is happening to the evolution of individual inclinations to choose an action when agents do interact ? Interaction tends to homogenize while each individual dynamics…

Probability · Mathematics 2020-08-05 Irene Crimaldi , Pierre-Yves Louis , Ida Germana Minelli

A semi-parametric, non-linear regression model in the presence of latent variables is applied towards learning network graph structure. These latent variables can correspond to unmodeled phenomena or unmeasured agents in a complex system of…

Machine Learning · Statistics 2018-07-03 Jonathan Mei , José M. F. Moura

We present an interacting-agent model of speculative activity explaining bubbles and crashes in stock markets. We describe stock markets through an infinite-range Ising model to formulate the tendency of traders getting influenced by the…

Statistical Mechanics · Physics 2009-10-31 Taisei Kaizoji