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Abridged abstract: Inert interactions between randomly moving entities and spatial disorder play a crucial role in quantifying the diffusive properties of a system. These interactions affect only the movement of the entities, and examples…

Statistical Mechanics · Physics 2022-09-20 Seeralan Sarvaharman , Luca Giuggioli

We study the dynamics of interacting agents from two distinct inter-mixed populations: One population includes active agents that follow a predetermined velocity field, while the second population contains exclusively passive agents, i.e.…

Numerical Analysis · Mathematics 2018-06-07 Matteo Colangeli , Adrian Muntean , Omar Richardson , Thoa Thieu

We analyze free energy functionals for macroscopic models of multi-agent systems interacting via pairwise attractive forces and localized repulsion. The repulsion at the level of the continuous description is modeled by pressure-related…

Analysis of PDEs · Mathematics 2018-12-18 J. A. Carrillo , M. G. Delgadino , F. S. Patacchini

This paper discusses the effect of sequential conflict resolution maneuvers of an infinite aircraft flow through a finite control volume. Aircraft flow models are utilized to simulate traffic flows and determine stability. Pseudo-random…

Optimization and Control · Mathematics 2010-10-05 Troy Hand , Zhi-Hong Mao , Eric Feron

We derive a class of macroscopic differential equations that describe collective adaptation, starting from a discrete-time stochastic microscopic model. The behavior of each agent is a dynamic balance between adaptation that locally…

Adaptation and Self-Organizing Systems · Physics 2024-05-15 Yuzuru Sato , Eizo Akiyama , James P. Crutchfield

Modelling of complex systems is mainly based on the decomposition of these systems in autonomous elements, and the identification and definitio9n of possible interactions between these elements. For this, the agent-based approach is a…

Artificial Intelligence · Computer Science 2013-02-27 Alain-Jérôme Fougères

A quest for uncovering influence of behaviour on team performance involves understanding individual behaviour, interactions with others and environment, variations across groups, and effects of interventions. Although insights into each of…

Physics and Society · Physics 2025-04-11 Hidemasa Ishii , Yohei Takai , Yuichiro Marui , Yoshihiro Yamazaki , Yusuke Kato , Hiroshi Kori

The solution of today's complex problems requires the grouping of task forces whose members are usually connected remotely over long physical distances and different time zones. Hence, understanding the effects of imposed communication…

Physics and Society · Physics 2017-02-15 Sandro M. Reia , Sebastian Herrmann , José F. Fontanari

The phase-field method is reviewed from the general perspective of converting a free boundary problem into a set of coupled partial differential equations. Its main advantage is that it avoids front tracking by using phase fields to locate…

This study investigates the concept of flexibility within League of Legends, a popular online multiplayer game, focusing on the relationship between user adaptability and team success. Utilizing a dataset encompassing players of varying…

Human-Computer Interaction · Computer Science 2026-03-18 Emily Chen , Alexander Bisberg , Emilio Ferrara

Recent research in multi-agent reinforcement learning (MARL) has shown success in learning social behavior and cooperation. Social dilemmas between agents in mixed-sum settings have been studied extensively, but there is little research…

Artificial Intelligence · Computer Science 2023-05-01 Ram Rachum , Yonatan Nakar , Reuth Mirsky

This paper introduces a crowd modeling and motion control approach that employs diffusion adaptation within an adaptive network. In the network, nodes collaboratively address specific estimation problems while simultaneously moving as…

Multiagent Systems · Computer Science 2023-10-25 Zirui Wan , Saeid Sanei

This paper introduces a paradigm shift by viewing the task of affect modeling as a reinforcement learning (RL) process. According to the proposed paradigm, RL agents learn a policy (i.e. affective interaction) by attempting to maximize a…

Machine Learning · Computer Science 2022-08-29 Matthew Barthet , Ahmed Khalifa , Antonios Liapis , Georgios N. Yannakakis

Workplace toxicity is widely recognized as detrimental to organizational culture, yet quantifying its direct impact on operational efficiency remains methodologically challenging due to the ethical and practical difficulties of reproducing…

Artificial Intelligence · Computer Science 2026-04-28 Benedikt Mangold

When two or more self-interested agents put their plans to execution in the same environment, conflicts may arise as a consequence, for instance, of a common utilization of resources. In this case, an agent can postpone the execution of a…

Artificial Intelligence · Computer Science 2015-03-05 Jaume Jordán , Eva Onaindia

Multi-agent systems offer a new and exciting way of understanding the world of work. We apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the…

Artificial Intelligence · Computer Science 2013-05-30 Peer-Olaf Siebers , Uwe Aickelin , Helen Celia , Chris Clegg

We explore the pressure of active particles on curved surfaces and its relation to other interfacial properties. We use both direct simulations of the active systems as well as simulations of an equilibrium system with effective (pair)…

Soft Condensed Matter · Physics 2019-05-14 René Wittmann , Frank Smallenburg , Joseph M. Brader

In cosmological first-order phase transitions, the microscopic interaction of the phase transition fronts with non-equilibrium plasma particles manifests itself macroscopically as friction forces. In general, it is a nontrivial problem to…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-15 Ariel Megevand

Recent advances in video generation have spurred the development of world models capable of simulating 3D-consistent environments and interactions with static objects. However, a significant limitation remains in their ability to model…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Anmol Agarwal , Pranay Meshram , Sumer Singh , Saurav Suman , Andrew Lapp , Shahbuland Matiana , Louis Castricato , Spencer Frazier

We analyze the adversarial examples problem in terms of a model's fault tolerance with respect to its input. Whereas previous work focuses on arbitrarily strict threat models, i.e., $\epsilon$-perturbations, we consider arbitrary valid…

Machine Learning · Computer Science 2018-12-03 Angus Galloway , Anna Golubeva , Graham W. Taylor
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