Article
Mathematics, Applied
Jinming Du, Ziren Wu
Summary: This study explores the emergence of cooperation between individuals in complex networked systems. Using the mathematical framework of evolutionary game theory and considering the dynamic changes in social networks, the researchers analyze the coevolution of strategy and network structure. They find that active self-recommendation by cooperators promotes cooperation, while higher self-recommendation intensity by defectors is detrimental to cooperation. Additionally, the competition between both sides leads to an increasing adjustment cycle.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Biology
Arne Traulsen, Nikoleta E. Glynatsi
Summary: Evolutionary game theory is an interdisciplinary subject that extends beyond biology, attracting mathematicians, social scientists, and computer scientists. The field has the potential for convergence or continued cross-fertilization between different disciplines, as insights are discovered and applied in various fields. The popularity of evolutionary game theory lies in its explanatory power and intuitive models.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2023)
Article
Physics, Multidisciplinary
Jinzhuo Liu, Yunchen Peng, Peican Zhu, Yong Yu
Summary: By introducing a mixed network coupling mechanism, we discovered a hump-like relationship between the level of cooperation and conservative participant density. The interspecies interactions promote cooperation between two types of players.
Article
Mathematics, Interdisciplinary Applications
Yong Shen, Wei Lei, Hongwei Kang, Mingyuan Li, Xingping Sun, Qingyi Chen
Summary: In public goods games, rewards have been shown to be an effective mechanism for sustaining cooperation. However, pure cooperators become second-order free-riders because they are not willing to bear additional costs. To address this issue, introducing a tax mechanism can effectively incentivize cooperation.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Jinxin Zhang, Meng Wu
Summary: In the blockchain network, individual participants cooperate by paying costs to maintain long-term stability, leading to a competitive game scenario. Researchers analyzed how participant behavior evolves with costs and payoffs, and its impact on the normal growth of the blockchain.
Article
Mathematics, Applied
Qing Jian, Xiaopeng Li, Juan Wang, Chengyi Xia
Summary: In this study, a novel donation game model was proposed to investigate the impact of reputation on the evolution of tag-mediated altruistic behaviors. The results indicate that the combination of reputation and tag greatly promotes the evolution of altruistic behaviors within a structured population, and the reputation threshold has a decisive effect on the dominant strategy within the population.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Mathematics, Interdisciplinary Applications
Tianyu Ren, Junjun Zheng
Summary: Altruistic sanctions play a crucial role in promoting cooperation in human society, and introducing a tolerance-based expulsion mechanism can significantly enhance cooperation, stabilize it under negative conditions, and determine the optimal threshold for implementation of expulsion.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Ecology
Daniel Wechsler, Jordi Bascompte
Summary: Mutualisms between flowering plants and pollinators are common in nature, but understanding their diversity and persistence is challenging. A model simulation reveals that cheating behavior promotes diversity and complex discrimination mechanisms in mutualistic relationships, but also increases the risk of collapse.
AMERICAN NATURALIST
(2022)
Article
Computer Science, Cybernetics
Hui Wei, Jianlei Zhang, Chunyan Zhang
Summary: This study investigates the coevolution of direct and indirect reciprocities and explores the emergence of indirect reciprocity through directional interactions. The results show that negative indirect reciprocity has stronger control property than other reciprocity strategies, and directionality can promote the emergence of indirect reciprocity.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Zhiyang Gu, Yu Xiao, Qin Cen, Rui Tao, Zhimin Liu, Shaoyu Zhou
Summary: The emergence of cooperation is a challenging problem, but can be promoted through a coevolution mechanism where individuals adjust the strength of their relationships with neighbors. Agent-based simulations show that cooperative behavior is greatly enhanced under this mechanism, with an optimal ratio of co-evolutionary individuals contributing to the evolution of cooperation.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Gaogao Dong, Shun Li, Ruijin Du, Qi Su
Summary: Population structure plays a crucial role in evolutionary dynamics by influencing interaction and strategy dispersal. Even individuals who are geographically and socially distant can learn from each other through social media. This study shows that disrupting the balance between interaction and dispersal networks can hinder cooperation, and increased network heterogeneity worsens this inhibitory effect. Furthermore, altering the dispersal network has a stronger impact on cooperation than modifying the interaction network.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Green & Sustainable Science & Technology
Chao Liu, Hexin Wang, Yu Dai
Summary: This paper constructs a tripartite evolutionary game model of schools, enterprises, and government to analyze the strategies and influencing factors of different players. The results indicate that the main factors influencing the stability of school and enterprise strategies are the rewards for positive cooperation from sources other than the government, and the main factor influencing government strategy stability is the benefits from a positive cooperation strategy under the scenario where schools cooperate with enterprises. Suggestions to promote sustainable cooperation between schools, enterprises, and government are proposed.
Article
Engineering, Mechanical
Zhihu Yang, Zhi Li
Summary: The oscillation of competing species is crucial for biodiversity, but evidence of oscillation in two-strategy games has been scarce. This study reveals the burst and transition of cooperation in a migration model driven by social norms, which is fundamentally different from conventional cyclic dominance found in games with more than three strategies. Adhering to norms and inequity aversion synergistically contribute to sustaining cooperation.
NONLINEAR DYNAMICS
(2022)
Article
Mathematics, Interdisciplinary Applications
Jianwei Wang, Fengyuan Yu, Jingyi Zhao, Fanfeng Li, Jialu He
Summary: Living in a competitive and risky environment, individuals pursue private interests and costly cooperation is abundant but voluntary sharing is hard to survive. The Temporary Interest Community (TIC) mechanism successfully rescues voluntary sharing and cooperation to some extent, but defection is never completely eliminated.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Industrial
Weihua Liu, Shangsong Long, Shuang Wei, Dong Xie, Jingkun Wang, Xinyun Liu
Summary: This study uses evolutionary game theory to describe the ecological cooperation between logistics platforms and suppliers, finding specific paths and suggestions for achieving ecological cooperation by adjusting parameters. The relationship between agency fees, empowerment costs, and service price elasticity coefficients determines the platform's ultimate stable strategy.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Theory & Methods
Kaijie Xu, Witold Pedrycz, Zhiwu Li
Summary: Granular Computing, an important technology in artificial intelligence, has received much attention in recent years. Fuzzy clustering, generating centroids and partition matrix, is a common way of information granulation. This study proposes an enhanced scheme to improve the quality of data reconstruction by modifying the partition matrix.
FUZZY SETS AND SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
TaiLong Jing, Cong Wang, Witold Pedrycz, ZhiWu Li, Giancarlo Succi, MengChu Zhou
Summary: This study proposes an approach to construct granular models based on information granules in input and output spaces, consisting of two stages: constructing information granules in the input space and analyzing and quantifying the relationship between input data and formed information granules. Experimental results demonstrate the superior performance of the proposed granular model on synthetic and publicly available datasets, with comparative analysis supporting its effectiveness.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Jianzhou Wang, Rui Wang, Zhiwu Li
Summary: An accurate hourly PM2.5 concentration prediction system is developed in this paper, based on advanced data processing, effective feature selection, and novel optimization algorithms. The simulation results demonstrate the system's excellent accuracy, generalization capability, and robust performance in predicting PM2.5 concentrations.
APPLIED SOFT COMPUTING
(2022)
Article
Automation & Control Systems
Jun Li, Dimitri Lefebvre, Christoforos N. Hadjicostis, Zhiwu Li
Summary: This article introduces a novel design principle for observers of timed discrete event systems that consider specific time semantics. By utilizing time stamps of observations, the state estimation process for labeled and timed automata can be refined, which has implications for estimation and inference tasks, as well as privacy and security issues. The article also discusses the promising application of the timed observer in the context of current-state opacity.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Green & Sustainable Science & Technology
Danxiang Wei, Jianzhou Wang, Zhiwu Li, Rui Wang
Summary: This paper proposes a hybrid copula-based wind power curve model (HCCM) that takes into account the relationship between wind speed and errors. Experimental results show that the proposed model significantly improves the accuracy of wind turbine forecasting.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Automation & Control Systems
Yao Lu, YuFeng Chen, ZhiWu Li, NaiQi Wu
Summary: Deadlocks in flexible manufacturing systems can be detected and resolved using a resource flow graph of a Petri net and a set of recovery transitions designed for loop graphs. This approach avoids generating a complete reachability graph of the Petri net and ensures that the resulting net is deadlock-free with all reachable markings.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Xubin Ping, Junying Yao, Baocang Ding, Zhiwu Li
Summary: This article proposes a solution for tube-based output feedback robust MPC for LPV systems, using offline and online optimization to design a lookup table, strengthen constraints, and scale terminal constraints. The recursive feasibility and robust stability of the controlled LPV system are guaranteed by ensuring convergence to the terminal constraint set and constraining uncertain state trajectories within robust tubes centered around the nominal system.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Cong Wang, Witold Pedrycz, ZhiWu Li, MengChu Zhou
Summary: This article introduces a Fuzzy C-Means (FCM) algorithm based on KL divergence, incorporating tight wavelet frame transform and morphological reconstruction. By introducing a KL divergence term on the partition matrix to make membership degrees closer, the algorithm improves image segmentation accuracy. Experimental results show that the proposed algorithm outperforms its peers in synthetic, medical, and real-world image segmentation, while also being faster than most FCM-related algorithms.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Xiubin Zhu, Witold Pedrycz, Zhiwu Li
Summary: This study elaborates on the realization of granular outputs for rule-based fuzzy models to effectively quantify modeling errors. The resulting granular model combines a regression model and an error model, with information granularity playing a central role. The quality of the produced interval estimates is evaluated using coverage and specificity criteria, and the optimal allocation of information granularity is determined.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Peng Nie, Xiubin Zhu, Witold Pedrycz, Zhengfeng Ming, Zhiwu Li
Summary: This study investigates the role of information granulation and degranulation in granular computing and how to reduce reconstruction error. Fuzzy clustering is used for the granulation process, and a novel neural network is leveraged to significantly reduce reconstruction error in the degranulation process. Experiments demonstrate the superiority of the proposed method in reconstructing original data.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Mathematics, Applied
Wei Chen, Qianlong Zhu, Te Wu
Summary: In this study, researchers investigated inequality in the context of the prisoner's dilemma. They found that extreme inequality and fairness were both ineffective in promoting cooperation, while moderate unfairness was the most favorable for cooperation under cyclic dominance. Additionally, the population evolved into a less unfair state when two strategies coexisted, and cooperators prevailed by acting fairer than defectors in a spontaneous manner. This work highlights the significant impact of inequality on the evolution of cooperation and emphasizes the importance of fairness and unfairness in enhancing cooperation.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Automation & Control Systems
Yufeng Chen, Lei Pan, Zhiwu Li
Summary: This paper proposes an iterative approach to separate a set of admissible markings of a nonlinear constraint into subsets. By using linear constraints, the admissible and inadmissible markings can be separated, and the given nonlinear constraint can be transformed into a set of disjunctive/conjunctive linear constraints. Furthermore, a method to design a Petri net supervisor for the constraints is proposed.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Xiaoguang Han, Jinliang Wang, Zhiwu Li, Xiaoyan Chen, Zengqiang Chen
Summary: This paper presents a new perspective on state estimation and weak detectability verification for discrete event systems. Two new matrix-based information structures are constructed using the semi-tensor product technique for computing different types of state estimates. The concept of weak delayed detectability is introduced, and various detectability problems are discussed. The proposed approaches are numerically tractable and can be implemented algorithmically. Examples are provided to illustrate the obtained results.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Yuxia Pan, Kaizhou Gao, Zhiwu Li, Naiqi Wu
Summary: This paper addresses a distributed lot-streaming permutation flow shop scheduling problem and proposes five meta-heuristics to solve it. Experimental results show that the artificial bee colony algorithm with improved strategies exhibits the best competitiveness for solving the problem with makespan criteria.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Xiubin Zhu, Dan Wang, Witold Pedrycz, Zhiwu Li
Summary: Designing effective and efficient classifiers is challenging due to the complexity of data structures and relationships. This study proposes a novel design methodology based on information granules, which leads to interpretable human-centric models with higher accuracy. The proposed models outperform commonly encountered classifiers and provide enhanced interpretability, as demonstrated by experiments on synthetic data and publicly available datasets.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
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)
