Article
Physics, Multidisciplinary
S. Arabzadeh, M. Sherafati, F. Atyabi, G. R. Jafari, K. Kulakowski
Summary: The paper investigates a fully connected network with signed links, considering the time evolution of the network towards a structurally balanced state. Results show that assigning a lifetime to each link leads to two asymptotic behaviors depending on the lifetime duration, with a crossover observed between them. The age distribution of links is found to depend on the lifetime, and the findings are discussed in the context of conflicts between political actors in Europe and the Middle East.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Tuan Minh Pham, Jan Korbel, Rudolf Hanel, Stefan Thurner
Summary: The robustness of social systems has long been connected to a triangular structure in social networks, where certain types of triples of individuals are overrepresented. A new study proposes a realistic adaptive network model that mimics this structure by allowing agents to minimize social tension through updating their opinions and relations based on local information. The model successfully predicts the distribution of triangle types and explains group size distributions, which are important for social cohesion.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Computer Science, Artificial Intelligence
Mingzhou Yang, Xingwei Wang, Lianbo Ma, Qiang He, Min Huang
Summary: This study proposes a novel structural balance model and designs an algorithm based on reinforcement learning to address the structural balance problem in signed social networks. Experimental results demonstrate that the algorithm outperforms other comparison algorithms in terms of optimal solutions, stability, and convergence.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Automation & Control Systems
Wenjun Mei, Ge Chen, Noah E. Friedkin, Florian Doerfler
Summary: This paper investigates how non-complete appraisal networks converge to structural balance while their graph topologies remain unchanged. Definitions of local balance and global balance are introduced, and two dynamics mechanisms are proposed to achieve local balance and global balance. Numerical studies provide insightful take-home messages.
Article
Computer Science, Artificial Intelligence
Temirlan Kalimzhanov, Amir Haji Ali Khamseh'i, Aresh Dadlani, Muthukrishnan Senthil Kumar, Ahmad Khonsari
Summary: This paper explores the impact of positive and negative relationships on the spread of viral phenomena in social networks. Using an energy model based on Heider's balance theory, the study reveals the trade-off between social tension and epidemic spread. The analysis also highlights the role of hostile social links in the formation of disjoint friendly clusters.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Physics, Applied
Wenqiang Duan, Qinma Kang, Yunfan Kang, Jianwen Chen, Qingfeng Qin
Summary: This study presents a simple and effective iterated greedy algorithm for solving structural balance problems. The algorithm aims to minimize frustration and achieves high efficiency through a constructive greedy heuristic, a two-stage local search procedure, an adaptive destruction method, and two acceleration methods. Experimental results show that the proposed algorithm outperforms other meta-heuristics in terms of computational time.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2022)
Article
Computer Science, Information Systems
Fanyuan Meng, Mathus Medo, Berno Buechel
Summary: This study tackles the problem of judging node types in signed networks, proposing a globally optimal Bayes solution and introducing a heuristic based on shortest paths to improve accuracy.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Yongqiang Guan, Aming Li, Long Wang
Summary: This article investigates the structural controllability of multiagent networks defined over directed signed graphs, deriving necessary and sufficient conditions for structural controllability and developing a method of polynomial complexity to achieve minimal structural controllability. Additionally, the structural controllability of specified networks and the application of theoretical results are discussed.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Physics, Fluids & Plasmas
Krzysztof Malarz, Janusz A. Holyst
Summary: By using the heat-bath approach and mean-field approximation, a critical temperature is analytically determined for a complete signed graph of N agents with time-dependent polarization of links approaching Heider balance. A discontinuous and irreversible phase transition is observed at this critical temperature, leading the system from a nearly balanced state to a disordered and unbalanced state. The system also exhibits a discontinuous phase transition at a lower temperature, where a balanced bipolar state decays towards disorder. The system phase diagram demonstrates a fold catastrophe with a hysteresis-like loop.
Article
Computer Science, Artificial Intelligence
Mingzhou Yang, Xingwei Wang, Lianbo Ma, Qiang He, Kexin Li, Min Huang
Summary: This paper proposes an improved structural balance model that considers the influence between nodes and the quality of the community. An enhanced multi-objective optimizer based on the non-dominated sorting genetic algorithm framework is designed to solve the model. The optimizer has a better ability to explore complex solution space and exploit local optimal regions quickly. A novel evaluation method is introduced to alleviate the computational complexity. The effectiveness and efficiency of the proposed algorithm are confirmed through experiments on different networks.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Information Systems
Roshni Chakraborty, Ritwika Das, Joydeep Chandra
Summary: This paper discusses the problem of signed link prediction in directed networks and proposes a GAN-based model called SigGAN. SigGAN considers the characteristics of directed networks, such as integration of negative edge information, imbalance in the number of positive and negative edges, and structural balance theory. Comparisons with state-of-the-art techniques on five real-world datasets validate the effectiveness of SigGAN.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2023)
Article
Computer Science, Artificial Intelligence
Zhihong Fang, Shaolin Tan, Yaonan Wang
Summary: In this paper, we propose a different link sign prediction architecture called SELO, which outperforms the state-of-the-art algorithm SDGNN in predicting the signs of links in signed networks. The SELO model utilizes a subgraph encoding approach to learn edge embeddings, achieving superior performance in evaluation metrics across six real-world signed networks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Arthur Capozzi, Alfonso Semeraro, Giancarlo Ruffo
Summary: Signed networks and balance theory provide a natural setting for studying polarization dynamics, positive/negative relationships, and political partisanship in real-world scenarios. This study proposes applying a pipeline to analyze and visualize a signed graph configuration based on the spectral properties of the corresponding Laplacian matrix. The proposed pipeline allows for the exploration of polarization dynamics and the influence of individual nodes or groups of congressmen in the overall balance of the U.S. Congress.
JOURNAL OF COMPLEX NETWORKS
(2023)
Article
Computer Science, Information Systems
Ya-Wei Niu, Cun-Quan Qu, Guang-Hui Wang, Jian-Liang Wu, Gui-Ying Yan
Summary: This study investigates information spreading with relative attributes on signed networks, proposing an algorithm and conducting simulations and experiments to show that information spreading can be approximately studied within a local 2-order neighborhood. Furthermore, the ratio of potential friendly nodes with a target node is related to network content, and 'good' information propagation speed unexpectedly slows down when the ratio of positive edges exceeds a certain threshold.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Giulia De Pasquale, Maria Elena Valcher
Summary: This paper investigates the herdability property of linear time-invariant state space models, focusing on the system's capability to be driven towards the positive orthant. The study explores the herdability of matrix pairs (A, B), where A represents the adjacency matrix of a multi-agent network and B is a selection matrix that identifies a subset of network leaders. It examines the cases when the associated graph G(A) is directed and clustering balanced or has a tree topology with a single leader.
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)