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State-space models are dynamical systems defined by a latent and an observed process. In ecology, stochastic state-space models in discrete time are most often used to describe the imperfectly observed dynamics of population sizes or animal…

Methodology · Statistics 2025-08-13 Frederic Barraquand , Julien Gibaud

How can we model influence between individuals in a social system, even when the network of interactions is unknown? In this article, we review the literature on the "influence model," which utilizes independent time series to estimate how…

Social and Information Networks · Computer Science 2012-02-28 Wei Pan , Manuel Cebrian , Wen Dong , Taemie Kim , James Fowler , Alex Pentland

We present a numerical method for learning the dynamics of slow components of unknown multiscale stochastic dynamical systems. While the governing equations of the systems are unknown, bursts of observation data of the slow variables are…

Machine Learning · Computer Science 2024-08-28 Yuan Chen , Dongbin Xiu

Active inference has emerged as an alternative approach to control problems given its intuitive (probabilistic) formalism. However, despite its theoretical utility, computational implementations have largely been restricted to…

Machine Learning · Computer Science 2022-03-01 Aswin Paul , Noor Sajid , Manoj Gopalkrishnan , Adeel Razi

Modeling how human moves in the space is useful for policy-making in transportation, public safety, and public health. Human movements can be viewed as a dynamic process that human transits between states (\eg, locations) over time. In the…

Artificial Intelligence · Computer Science 2021-03-24 Hua Wei , Dongkuan Xu , Junjie Liang , Zhenhui Li

In this paper, we study collective interaction dynamics emerging in the game of football-soccer. To do so, we surveyed a database containing body-sensors traces measured during three professional football matches, where we observed…

Physics and Society · Physics 2021-08-18 A. Chacoma , N. Almeira , J. I. Perotti , O. V. Billoni

Adaptive user interfaces adapt their contents, presentation, or behavior mostly in a sudden, fluctuating, and abrupt way, which may cause negative effects on the end users, such as cognitive disruption. Instead, adaptivity should be…

Human-Computer Interaction · Computer Science 2024-12-18 Alaa Eddine Anis Sahraoui

We present a survey of recent research studies of the implementation of adaptive user models in human-computer interaction. A classification of research directions on adaptive user interfaces is first proposed; it takes account of the user…

Human-Computer Interaction · Computer Science 2007-08-29 Jérôme Simonin , Noëlle Carbonell

In this paper, the new information system development methodology will be proposed. This methodology will enable the whole data model to be built and adjusted at the run time, without rebuilding the application. This will make the user much…

Software Engineering · Computer Science 2011-02-01 Vojtech Prehnal

Recent trends in information management involve the periodic transcription of data onto secondary devices in a networked environment, and the proper scheduling of these transcriptions is critical for efficient data management. To assist in…

Databases · Computer Science 2007-05-23 Avigdor Gal , Jonathan Eckstein

We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The…

Probability · Mathematics 2007-05-23 Brian Skyrms , Robin Pemantle

This paper considers some designs for sampling and interventions in dynamic networks and spatial temporal settings. The sample spreads through the population largely by tracing network links, although random sampling or spatial designs may…

Methodology · Statistics 2013-06-05 Steven K. Thompson

Methods that detect user states such as emotions are useful for interactive systems. In this position paper, we argue for model-based approaches that are trained on user behaviour and self-reported user state as ground truths. In an…

Human-Computer Interaction · Computer Science 2020-07-30 Julian Frommel , Regan L Mandryk

In modern science, computer models are often used to understand complex phenomena, and a thriving statistical community has grown around analyzing them. This review aims to bring a spotlight to the growing prevalence of stochastic computer…

To protect the systems exposed to the Internet against attacks, a security system with the capability to engage with the attacker is needed. There have been attempts to model the engagement/interactions between users, both benign and…

Cryptography and Security · Computer Science 2018-01-19 Vivek Shandilya , Sajjan Shiva

The physical sciences are replete with dynamical systems that require the resolution of a wide range of length and time scales. This presents significant computational challenges since direct numerical simulation requires discretization at…

Machine Learning · Computer Science 2025-11-11 Andrew F. Ilersich , Prasanth B. Nair

We discuss several models of the dynamics of interacting populations. The models are constructed by nonlinear differential equations and have two sets of parameters: growth rates and coefficients of interaction between populations. We…

Adaptation and Self-Organizing Systems · Physics 2013-07-29 Nikolay K. Vitanov , Zlatinka I. Dimitrova

Software developers cannot always anticipate how users will actually use their software as it may vary from user to user, and even from use to use for an individual user. In order to address questions raised by system developers and…

Software Engineering · Computer Science 2014-03-27 Oana Andrei , Muffy Calder , Matthew Higgs , Mark Girolami

When designing systems that are complex, dynamic and stochastic in nature, simulation is generally recognised as one of the best design support technologies, and a valuable aid in the strategic and tactical decision making process. A…

Neural and Evolutionary Computing · Computer Science 2013-05-30 Peer-Olaf Siebers , Uwe Aickelin

Many stochastic physical systems evolve smoothly over time in the sense that the distribution of states changes regularly across time steps. The transition from current state to the next state can often be modeled as the combination of a…

Machine Learning · Computer Science 2026-05-29 Jules Berman , Tobias Blickhan , Benjamin Peherstorfer