Cooperative Problem Research Articles

The Transportation Cooperation Between Northeast China and the Russian Far East Under the Russia-Ukraine War

The logistics and transportation system of Russia and the world was greatly affected by the 2022 Russia-Ukraine war and the sanctions under the war. Under such circumstances, Sino-Russian cooperation in cross-border transportation is of great significance for the operation of international logistics system and the high-quality cooperation between China and Russia. The aim of this research is to find feasible paths for the transportation cooperation between Northeast China and Russian Far East by analyzing the current situation and existing problems in international transportation cooperation between the two regions. It was found that the current feasible paths of transportation cooperation between Northeast China and Russian Far East include: (1) carrying out transportation cooperation through “pivot cities”; (2) strengthening transportation cooperation by Russian Far East’s Territories of Advanced Development; (3) seizing the new opportunities of Harbin’s opening up to the north to promote international transportation cooperation with Russia; (4) developing transportation cooperation through the linking cooperation between the “Belt and Road” and the “Eurasian Economic Union”.

Cooperative attack strategy during the terminal guidance phase for loitering munitions based on impact angle and impact time constraints

In order to solve the cooperative attack problem during the terminal guidance phase for loitering munition swarm, a cooperative attack strategy for loitering munitions with impact angle constraints is proposed. By using the small deviation method, an offset proportional guidance law with impact angle constraints is derived in order to solve the problem of directional strike in the longitudinal plane. Combining with the present guidance scheme, a method for estimating the remaining time of proportional control and angle control is derived. In the lateral plane, a time control bias term with time-varying coefficients and no singularity in the division of zero is designed to solve the time control problem. In addition, taking the remaining time as the coordination variable, a two-layer cooperative architecture is used to solve the problem of coordinated directional strike of multiple loitering munitions. The simulation results show that the cooperative guidance strategy has a good performance of impact angle control and cooperative attack for low-speed loitering munitions.

Robust distributed fixed-time cooperative hunting control for multi-quadrotor with obstacles avoidance

This paper addressed the robust distributed fixed-time cooperative hunting problem of multiple quadrotors subject to disturbances in obstacles environment. To handle the underactuated issue inherent in quadrotor dynamics, an inner–outer (attitude-position) loop cascade control configuration is proposed to achieve the cooperative flight control of quadrotors. For position subsystem, as the information of target cannot be accessible to all quadrotors, a distributed fixed-time observer is devised to estimate the target’s information. To improve the system’s robustness, a fixed-time extended state observer is designed to reject disturbances actively. Based on two observers, the sliding mode position encirclement control protocol with repulsive force is presented to avoid obstacles and encircle the target within a fixed time. For attitude subsystem, a sliding mode attitude tracking control protocol is proposed such that tracking errors can converge to zero even under disturbances. The stability analysis is performed to show the stabilization of the whole closed-loop system with fixed-time convergence. Finally, two sets of comparison simulation are provided to show the superiority of the developed control strategy.

Study on International Cooperation to Address Cross-border Telecommunication Network Fraud Offence

In recent years, under the new technological environment of the international society, cross-border telecommunication network fraud crime cases are high, and various countries are faced with difficult problems of law enforcement cooperation, such as: less channels of information exchange, difficult investigation and evidence collection, low efficiency, more obstacles to investigation and arrest cooperation, slow speed and low effectiveness of recovering stolen goods. In order to achieve effective international governance of cross-border network crimes and strengthen cooperation between China and other countries, this study is based on the collection of cross-border telecommunication network fraud crimes of international cooperation cases and literature, combined with the current situation of cross-border international cooperation in China, proposed to effectively solve the problem of cross-border telecommunication network fraud international cooperation from the prevention and governance level. In order to achieve a higher level of international cooperation and governance between countries, and continuously reduce the occurrence of cross-border telecommunication network fraud cases.

The Importance of Interdisciplinary Collaboration in the Field of Special Education in Greece

The issue of the cooperation of all experts in the field of education is a very important element that significantly affects the effectiveness of the educational project. Although for many it is taken for granted, it is not at all easy to realize. The purpose of this paper is to highlight how teachers, including social workers, who work in special education structures in Greece perceive this issue. To elicit the discourse of specialized professionals, ten semi-structured interviews were conducted with teachers, social workers, and psychologists in the context of qualitative research and thematic content analysis. The results highlight useful information related to what is happening today in the field of education. They focus on the experiences of the professionals themselves on the one hand with each other, on the other with the parents, and the supportive environment of the students. The results yield very valuable information about how professionals try to achieve what is called integrated intervention. Uniquely, the difficulties of professional everyday life are captured and at the same time, an attempt is made to highlight ways of effective management of cooperation problems.

Volt-VAR Control in Active Distribution Networks Using Multi-Agent Reinforcement Learning

With the advancement of power systems, the integration of a substantial portion of renewable energy often leads to frequent voltage surges and increased fluctuations in distribution networks (DNs), significantly affecting the safety of DNs. Active distribution networks (ADNs) can address voltage issues arising from a high proportion of renewable energy by regulating distributed controllable resources. However, the conventional mathematical optimization-based approach to voltage reactive power control has certain limitations. It heavily depends on precise DN parameters, and its online implementation requires iterative solutions, resulting in prolonged computation time. In this study, we propose a Volt-VAR control (VVC) framework in ADNs based on multi-agent reinforcement learning (MARL). To simplify the control of photovoltaic (PV) inverters, the ADNs are initially divided into several distributed autonomous sub-networks based on the electrical distance of reactive voltage sensitivity. Subsequently, the Multi-Agent Soft Actor-Critic (MASAC) algorithm is employed to address the partitioned cooperative voltage control problem. During online deployment, the agents execute distributed cooperative control based on local observations. Comparative tests involving various methods are conducted on IEEE 33-bus and IEEE 141-bus medium-voltage DNs. The results demonstrate the effectiveness and versatility of this method in managing voltage fluctuations and mitigating reactive power loss.

Multi‐event‐based distributed cooperative predictive control for the multi‐agent system

AbstractIn this paper, we provide the detailed distributed cooperative predictive control scheme for the multi‐agent system (MAS) affected by the network delays. Firstly, we restate the distributed cooperative predictive control problem by introducing iterative learning‐based MAS, which can guarantee the cooperative predictive control of the MAS. To alleviate the unfavorable network constrains, the multi‐event‐triggered conditions are formulated via considering the predictive and error data sufficiently. With these preparations, the well‐posed Roesser‐type two‐dimensional (2D) system is achieved equivalently to the distributed iterative learning predictive system. On this basis, we employ 2D predictive system analysis and control theory to realize the predictive control for the equivalent 2D system and then obtain the collaborative predictive control for the MAS under multi‐event‐triggered mechanism. The corresponding stability criteria, controller, and observer gains are provided by the executable matrix constraints and algorithms design. To conclude the paper, the numerical example is proposed to illustrate the effectiveness and practicability of the provided methods and algorithms.

Multi-USV cooperative oil spill source seeking via extremum seeking combined with information fusion

This paper addresses the issue of cooperative source seeking for oil spill pollution by multiple unmanned surface vehicles (USVs), where the oil spill plume propagation is modeled by a linear advection–diffusion equation in two-dimensional space. The main objective is to construct a cooperative source seeking scheme for a group of USVs in the framework of extremum seeking combined with information fusion to solve such cooperative source seeking problem. To do this, both a gradient-based control law and a formation control law are included in the cooperative source seeking scheme. The gradient-based control law that is constructed by extremum-seeking control combined with information fusion drives the multiple USVs to approach the oil spill source, where the gradient is estimated online via the extremum-seeking control and the fused concentration value that is derived via a linear H∞ filter from the local concentration measurements at the USV’s current position. In the source seeking process, the USVs driven by the formation control law based on the virtual structure method maintain a preset circular formation. The convergence performance of the cooperative source seeking scheme is analyzed rigorously by the Lyapunov method. Finally, extensive numerical simulations are included to validate the theoretical algorithm.

Impact of trans-regional travel-related testing on epidemic spreading

The convenient transport network enables people to travel quickly and frequently across regions, but it also brings serious challenges to the emergency management of infectious diseases. This work extends the classical SEIR model by incorporating trans-regional population movements and contact infections during travel. It also includes cross-regional population testing and treatment measures to curb the spread of infectious diseases across regions. According to these characteristics, a Net-SEIHR model is established and its diffusion properties are deduced. Further, the cooperative allocation problem of limited detection resources and its control strategy are discussed. Numerical experiments show that the control measures can reduce the speed of trans-regional transmission of infectious diseases and the peak of treatment. In the case of limited testing resources, it is necessary to strengthen the detection of people in the inflow regions.

Evolutionary game analysis on cross-border cooperative R&D of intelligent new energy vehicle industry

PurposeIntelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.Design/methodology/approachThe authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.FindingsResults showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.Research limitations/implicationsThe research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.Originality/valueThe INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

Global AI governance: barriers and pathways forward

Abstract Recent advances in artificial intelligence (AI), combined with a proliferation in use, have led to a newfound emphasis on strengthening the global governance of AI. In this article, we assess the prospects for stronger global AI governance and consider potential pathways forward. We map the nascent landscape of international regimes focused on AI governance and conclude that a governance deficit remains due to the inadequacy of existing initiatives, gaps in the landscape and difficulties reaching agreement over more appropriate mechanisms. First-order cooperation problems stemming from interstate competition and second-order cooperation problems from dysfunctional international institutions problematize overcoming current deficiencies in global AI governance. In light of these cooperation problems, we evaluate two pathways for strengthening global AI governance: (a) developing new centralized international AI institution(s); and (b) strengthening coordination between, and capacities of, existing institutions. We argue that strengthening the existing weak ‘regime complex’ of international institutions is the more politically legitimate and viable path forward. Improving coordination between, and capacities of, existing international institutions governing AI would support inclusive and mutually reinforcing policy change that can mitigate a range of risks associated with these technologies. As first steps for strengthening the weak AI regime complex, we recommend that the OECD is foregrounded as a centre of expert AI knowledge so that it can facilitate peer pressure among states and harmonization of policies. We also encourage scrutiny of different nodes in the regime complex to ensure that they are fulfilling appropriate functions based on their democratic mandates.

Collective action problems in planetary defense

In recent years, growing awareness of potential threats posed by near-Earth objects (NEOs) has led to increased interest in developing and implementing planetary defense measures. International cooperation and public support are crucial to ensuring the long-term success of planetary defense initiatives. However, a number of economic, political, legal, and social issues stand in the way of effective large-scale cooperation in pursuing planetary defense. This article examines the major challenges to international cooperation in planetary defense. The article begins by considering the major types of collective action problems facing international collaboration toward planetary defense. The article then examines the way in which adjacent space-related aspects of international affairs influence the arena of planetary defense. The article then analyzes the legal aspects of these cooperation problems, focusing on sources of perceived uncertainty that interfere with effective development of norms for cooperation. The article then proposes various possible strategies for avoiding cooperation problems and increasing collective buy-in. Noteworthy examples include the use of treaties as pre-commitment devices (which parties agree to undertake in order to limit their future options and commit themselves to pre-established lines of conduct) and amendments to existing legal frameworks to decrease perceived uncertainty and promote objective standards of cooperation. The article concludes by reflecting on the importance of promoting a widespread cultural perspective that emphasizes the pursuit of collective planetary welfare over competing national interests.

Multiple-stage spatial–temporal cooperative guidance without time-to-go estimation

This paper investigates the spatial–temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information. First, a two-stage cooperative guidance strategy, namely the cooperative guidance and the Proportional Navigation Guidance (PNG) stage strategy, is developed to realize the spatial–temporal constraints in two dimensions. At the former stage, two controllers are designed and superimposed to satisfy both impact time consensus and impact angle constraints. Once the convergent conditions are satisfied, the flight vehicles will switch to the PNG stage to ensure zero miss distance. To further extend the results to three dimensions, a planar pursuit guidance stage is additionally imposed at the beginning of guidance. Due to the independence of time-to-go estimation, the proposed guidance strategy possesses great performance in satisfying complex spatial–temporal constraints even under flight speed variation. Finally, several numerical simulations are implemented to verify the effectiveness and advantages of the proposed results under different scenarios.

중국의 아세안 전략과 경제협력의 특징과 문제 -메콩개발과 일대일로를 중심으로

중국의 아세안 전략과 경제협력의 특징과 문제 -메콩개발과 일대일로를 중심으로

Perception of safety and cooperativeness among police officers serving in public areas, and identification of public security problems in Fejér County

Aim: As part of Árpád Budavári’s doctoral research entitled “Chances of police reform and community-based” policing, the authors conducted a survey in 2020–2021 among the police officers serving in the public areas of the Fejér County Police Headquarters, to investigate the policemen’s understanding of security, their cooperativeness, and to identify of public security problems in Fejér county. Methodology: The hypothesis of the survey is that the police show signs of cooperative problem solving with communities in society, and it is also possible to identify intervention needs that can improve the problem sensitivity and cooperative competences of the police. The results of the survey on a sample 310 policemen were compared with the results of a survey on a sample of 500 citizens in Székesfehérvár conducted in 2016, which was used to assess the extent to which the understanding of security and the perception of security actors are the same and the extent to which they differ between the two target groups. Findings: The results of the survey clearly show the recognition of the importance of cooperation with the public and the demand for cooperation. It is observed, however, that this is hindered by several factors. It can also be concluded that members of police do not currently recognise the importance and effectiveness of public security institutions other than the police. Further research is needed to reveal the reasons behind this phenomenon. Value: By comparing the opinions of the police with those of the public, and by revealing the willingness of police officers to cooperate, the research results will contribute to the diagnosis of the state of the police and to the identification of the needs for change.

Effectiveness of Cooperative Problem Solving on Energy Concept in Physics Learning for Improving Students' Creative Thinking Skills

This study aimed to determine the effectiveness of the cooperative problem solving learning model in improving students’ creative thinking skills on the concept of energy. The research method used is a quasi-experimental design with a pretest-posttest nonequivalent control group design. The research was conducted at Garut. The research population were students of class X MIA 1-10. The sampling technique used was cluster random sampling. A total of 60 students of class X MIA 1 and 9 were selected, (41 female and 19 male). Students’ creative thinking ability is obtained from pretest and posttest in the form of an essay test of 12 questions. The improvement of each student’s creative thinking skills (Torrance) indicators to the concept of energy was obtained from the calculation of N-Gain with the values of smoothness (0.85), flexibility (0.56), and elaboration (0.72). The effectiveness of the learning model was tested using t-test hypothesis with the assistance of the SPSS version 28 proving that there is an increase in creative thinking skills after the implementation of cooperative problem-solving learning model on energy concept. Thus, the cooperative problemsolving learning model is very effective to be used as a solution in improving students’ creative thinking skills. Keywords: cooperative problem solving, energy concept, creative thinking skills

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.

GHQ: grouped hybrid Q-learning for cooperative heterogeneous multi-agent reinforcement learning

Previous deep multi-agent reinforcement learning (MARL) algorithms have achieved impressive results, typically in symmetric and homogeneous scenarios. However, asymmetric heterogeneous scenarios are prevalent and usually harder to solve. In this paper, the main discussion is about the cooperative heterogeneous MARL problem in asymmetric heterogeneous maps of the Starcraft Multi-Agent Challenges (SMAC) environment. Recent mainstream approaches use policy-based actor-critic algorithms to solve the heterogeneous MARL problem with various individual agent policies. However, these approaches lack formal definition and further analysis of the heterogeneity problem. Therefore, a formal definition of the Local Transition Heterogeneity (LTH) problem is first given. Then, the LTH problem in SMAC environment can be studied. To comprehensively reveal and study the LTH problem, some new asymmetric heterogeneous maps in SMAC are designed. It has been observed that baseline algorithms fail to perform well in the new maps. Then, the authors propose the Grouped Individual-Global-Max (GIGM) consistency and a novel MARL algorithm, Grouped Hybrid Q-Learning (GHQ). GHQ separates agents into several groups and keeps individual parameters for each group. To enhance cooperation between groups, GHQ maximizes the mutual information between trajectories of different groups. A novel hybrid structure for value factorization in GHQ is also proposed. Finally, experiments on the original and the new maps show the fabulous performance of GHQ compared to other state-of-the-art algorithms.

Robust Cooperative Fault-Tolerant Control for Uncertain Multi-Agent Systems Subject to Actuator Faults.

This article investigates the robust cooperative fault-tolerant control problem of multi-agent systems subject to mismatched uncertainties and actuator faults. During the design process of the intermediate variable estimator, there is no need to satisfy fault estimation matching conditions, and this overcomes a crucial constraint of traditional observers and estimators. The feedback term of the designed estimator contains the centralized estimation errors and the distributed estimation errors of the agent, and this further improves the design freedom of the proposed estimator. A novel fault-tolerant control protocol is designed based on the fault estimation information. In this work, the bounds of the fault and its derivatives are unknown, and the considered method is applicable to both directed and undirected multi-agent systems. Furthermore, the parameters of the estimator are determined through the resolution of a linear matrix inequality (LMI), which is decoupled by employing coordinate transformation and Schur decomposition. Lastly, a numerical simulation result is used to demonstrate the effectiveness of the proposed method.

Multi-robot Source Navigation Method Based on Coordination Graph Monte Carlo Tree Search

To address the dynamic cooperative multi-robot sequential decision problem, we propose a multi-robot source navigation method based on coordination graph Monte Carlo tree search. The Monte Carlo tree search online planning is designed with the algorithm system's structure in mind. We combine the upper confidence bound strategy with the coordination graph, which represents multi-robot cooperative communication, and solve the coordination graph using the max-sum algorithm to select joint actions. This paper proposes a time series prediction model for optimizing multi-robot movement trends using historical data, which is then used to solve the exploration and exploitation problem in Monte Carlo tree search. The experimental analysis and comparison show that our proposed method outperforms the comparison algorithms in terms of source search steps, task execution time, and source search success rate, as well as robustness and efficiency for multi-robot source search.