Complex field network-coded cooperation based on multi-user detection in wireless networks

Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.

Research on Cognitive Cooperation in Multi-Agent Systems

The accomplishment of a complex problem usually involves cooperation between participators with different knowledge background concerned. This paper identifies interdependency between different sub problems （through problem decomposition） as the major factor that influences cooperative relations in multi-Agent systems, based on which we propose an efficient means to measure cooperation coefficient （degree） between different Agents. Then cognitive cooperation between Agents is analyzed which aims at collecting the wisdom of the cognitive community for a systematic solution to the overall problem.

Receiver-Controlled Multi-Node Cooperation

Since wireless links in Ad hoc networks are more fragile than those in traditional wireless networks due to route flapping,multi-node cooperation plays an important role in ensuring the quality of service( QoS). Based on the authors' previous work,this paper proposes a receiver-controlled multi-node cooperation routing protocol,known as AODV-RCC. In this protocol,nodes form a cooperation group based on signal power. In a cooperation group,signal power between a partner and a transmitter,as well as signal power between the partner and the receiver,must be larger than the signal power between the transmitter and the receiver. Otherwise,the transmission will not benefit from cooperation. To avoid collision or congestion,each cooperation group only contains one partner. This partner offers both data and ACK cooperative retransmission. Its retransmission time should be shorter than the internal retry time of the transmitter's MAC layer,because it is better for the partner to retransmit firstly,as it offers a more reliable cooperative link. In AODV-RCC,it is the receiver that chooses the partner,because the link between the partner and the receiver is the most important. According to our simulation results,AODV-RCC shortens the end-to-end delay and increases the packet delivery ratio.

Rough set based multi-agent system cooperation for industrial supervisory interface system

In this paper, rough set theory is introduced into the interface multi-agent system （MAS） for industrial supervisory system. Taking advantages of rough set in data mining, a cooperation model for MAS is built. Rules for avoiding cooperation conflict are deduced. An optimization algorithm is used to enhance security and real time attributes of the system. An application based on the proposed algorithm and rules are given.

Multi-level Cooperation and Complementary Advantage Poverty Alleviation Model in Poverty-Stricken Counties of Tibetan Areas:A Case Study of Songpan County in Sichuan Province

Songpan County is a poverty-stricken county in Tibetan areas of Sichuan Province,it belongs to a concentrated poverty-stricken area in China.Through summarizing the specific conditions of multi-level cooperation and complementary advantage poverty alleviation model in Songpan County,this paper analyzed the effect of this model.Through the analysis on the cooperative poverty alleviation model(eastern-western cooperation,provincial targeted assistance,county-wide"four-leading and four-assistance"inner-party assistance,social force"10000 enterprises helping 10000 villages",and"visiting every household and keeping every person busy"),it summarized the implementation and actual results of each level.In addition,it summarized the problems encountered in the implementation process of multi-level cooperation and complementary advantage poverty alleviation model and came up with recommendations.With the aid of this successful multi-level cooperation and complementary advantage poverty alleviation model,Songpan County has achieved a decisive victory in the fight against poverty.At the end of April 2019,the poverty rate in the whole region fell to 0.45%,and it successfully took off the poverty hat.This paper analyzed and refined the specific practice,main achievements,successful experience,implications and reference significance of multi-level cooperation and complementary advantage poverty alleviation model,to provide necessary references for innovation of poverty alleviation model in poverty-stricken Tibetan areas,or even other similar provinces and regions.

基于Multi-Agent的无人机集群体系自主作战系统设计

针对无人集群自主作战体系设计中的关键问题,提出基于Multi-Agent的无人集群自主作战系统设计方法。建立无人集群各节点的Agent模型及其推演规则;对于仿真系统模块化和通用化的需求,设计系统互操作式接口和无人集群自主作战的交互关系;开展无人集群系统仿真推演验证。仿真结果表明,所提设计方案不仅能够有效开展并完成自主作战网络生成-集群演化-效能评估的全过程动态演示验证,而且能够通过重复随机试验进一步评估无人集群的协同作战效能,最后总结了集群协同作战的策略和经验。

Coalition Formation for Multiple UAVs Cooperative Search and Attack with Communication Constraints in Unknown Environment

A coalition formation algorithm is presented with limited communication ranges and delays in unknown environment,for the performance of multiple heterogeneous unmanned aerial vehicles(UAVs)in cooperative search and attack missions.The mathematic model of coalition formation is built on basis of the minimum attacking time and the minimum coalition size with satisfying resources and simultaneous strikes requirements.A communication protocol based on maximum number of hops is developed to determine the potential coalition members in dynamic network.A multistage sub-optimal coalition formation algorithm(MSOCFA)with polynomial time is established.The performances of MSOCFA and particle swarm optimization(PSO)algorithms are compared in terms of complexity,mission performance and computational time.A complex scenario is deployed to illustrate how the coalitions are formed and validate the feasibility of the MSOCFA.The effect of communication constraints(hop delay and max-hops)on mission performance is studied.The results show that it is beneficial to determine potential coalition members in a wide and deep range over the network in the presence of less delay.However,when the delays are significant,it is more advantageous to determine coalitions from among the immediate neighbors.

Innovatory technical cooperation between Sino-Russian lndustries

Discusses the necessity for China and Russia to change the existing small scale and level bilateral economic and trade relations for better by breaking away from traditional thoughts and formulating new thoughts on development of economic and trade relations between the two countries, and suggests the need to develop all azimuth and multi level economic and trade relations with emphasis on industrial cooperations to develop the leading industries of these two countries in accord with the strategic partnership between these two countries for the 21 century to suit the changes in the formation of new multi pole international order, and concludes the industries in these two countries can be made structurally complementary to each other and coexistent with the leading industries by developing steady and reliable industrial cooperative relations to further strengthen the strategic partnership between the two countries.

A Distributed Cooperative Localization Algorithm for Mobile Multi-platforms Oriented to Unpredicted Communication Topology

The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is investigated.To improve the adaptability,the character of the look-up Cholesky decomposition is exploited for the covariance matrix decomposing.Then,the distributed U transformation can be dynamically implemented according to the available communication topology.In the proposed algorithm,the global information is not required for the individual,and only the available information from the neighbor is used.Each platform’s state can be estimated independently.The error covariance of the state estimates can be updated in the single platform.The algorithm is adaptive to any serial communication topologies where the measuring to the measured platform is a starting path.The applicability of the proposed algorithm to unpredicted communication topology is improved,remaining equivalent localization performance to free connection communication.

Immune multi-agent model using vaccine for cooperative air-defense system of systems for surface warship formation based on danger theory

Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.

Fuzzy Timed Agent Based Petri Nets for Modeling Cooperative Multi-Robot Systems

A cooperative multi-robot system (CMRS) modeling method called fuzzy timed agent based Petri nets (FTAPN) is proposed in this paper, which has been extended from fuzzy timed object-oriented Petri net (FTOPN). The proposed FTAPN can be used to model and illustrate both the structural and dynamic aspects of CMRS, which is a typical multi-agent system (MAS). At the same time, supervised learning is supported in FTAPN. As a special type of high-level object, agent is introduced into FTAPN, which is used as a common modeling object in its model. The proposed FTAPN can not only be used to model CMRS and represent system aging effect, but also be refined into the object-oriented implementation easily. At the same time, it can also be regarded as a conceptual and practical artificial intelligence (AI) tool for multi-agent systems (MAS) into the mainstream practice of the software development.

The Coalition Cooperative Game Method and Its Application in Multi-objective Optimization Design

This paper proposes a multi-objective optimization design method based on the coalition cooperative game theory where the three design goals have been seen as three game players. By calculating the affecting factors and fuzzy clustering, the design variables are divided into different strategic spaces which belong to each player, then it constructs a payoff function based on the coalition mechanism. Each game player takes its own revenue function as a target and obtains the best strategy versus other players. The best strategies of all players consist of the strategy permutation of a round game and it obtains the final game solutions through multi-round games according to the convergence criterion. A multi-objective optimization example of the luff mechanism of compensative sheave block shows the effectiveness of the coalition cooperative game method.

Method of distribution and cooperation for electro-optical countermeasures jamming resources

The concept of the method resource is introduced to deal with the cooperative application problem of different electro-optical countermeasure equipments. Based on this concept, a new approach is introduced to distribute the jamming resources of electro-optical countermeasures, and it is used to deploy and manage electro-optical countermeasures resources under the restriction conditions of cooperation and incompatibility disposing. The resource management procedure is formalized by Finite State Machine (FSM). By using the cooperative resource operation system on the basis of multi-agent systems, a complex system with three incompatible swarms is constructed and cooperative operation procedures are demonstrated by simulations.

Cooperative Multi-Agent Reinforcement Learning with Constraint-Reduced DCOP

Cooperative multi-agent reinforcement learning（ MARL） is an important topic in the field of artificial intelligence,in which distributed constraint optimization（ DCOP） algorithms have been widely used to coordinate the actions of multiple agents. However,dense communication among agents affects the practicability of DCOP algorithms. In this paper,we propose a novel DCOP algorithm dealing with the previous DCOP algorithms＇ communication problem by reducing constraints.The contributions of this paper are primarily threefold：（1） It is proved that removing constraints can effectively reduce the communication burden of DCOP algorithms.（2） An criterion is provided to identify insignificant constraints whose elimination doesn＇t have a great impact on the performance of the whole system.（3） A constraint-reduced DCOP algorithm is proposed by adopting a variant of spectral clustering algorithm to detect and eliminate the insignificant constraints. Our algorithm reduces the communication burdern of the benchmark DCOP algorithm while keeping its overall performance unaffected. The performance of constraint-reduced DCOP algorithm is evaluated on four configurations of cooperative sensor networks. The effectiveness of communication reduction is also verified by comparisons between the constraint-reduced DCOP and the benchmark DCOP.

Evaluation of Linear Precoding Schemes for Cooperative Multi-Cell MU MIMO in Future Mobile Communication Systems

In Mobile Communication Systems, inter-cell interference becomes one of the challenges that degrade the system’s performance, especially in the region with massive mobile users. The linear precoding schemes were proposed to mitigate interferences between the base stations (inter-cell). These schemes are categorized into linear and non-linear;this study focused on linear precoding schemes, which are grounded into three types, namely Zero Forcing (ZF), Block Diagonalization (BD), and Signal Leakage Noise Ratio (SLNR). The study included the Cooperative Multi-cell Multi Input Multi Output (MIMO) System, whereby each Base Station serves more than one mobile station and all Base Stations on the system are assisted by each other by shared the Channel State Information (CSI). Based on the Multi-Cell Multiuser MIMO system, each Base Station on the cell is intended to maximize the data transmission rate by its mobile users by increasing the Signal Interference to Noise Ratio after the interference has been mitigated due to the usefully of linear precoding schemes on the transmitter. Moreover, these schemes used different approaches to mitigate interference. This study mainly concentrates on evaluating the performance of these schemes through the channel distribution models such as Ray-leigh and Rician included in the presence of noise errors. The results show that the SLNR scheme outperforms ZF and BD schemes overall scenario. This implied that when the value of SNR increased the performance of SLNR increased by 21.4% and 45.7% for ZF and BD respectively.

Multi-Feature Fusion Based Relative Pose Adaptive Estimation for On-Orbit Servicing of Non-Cooperative Spacecraft

On-orbit servicing, such as spacecraft maintenance, on-orbit assembly, refueling, and de-orbiting, can reduce the cost of space missions, improve the performance of spacecraft, and extend its life span. The relative state between the servicing and target spacecraft is vital for on-orbit servicing missions, especially the final approaching stage. The major challenge of this stage is that the observed features of the target are incomplete or are constantly changing due to the short distance and limited Field of View (FOV) of camera. Different from cooperative spacecraft, non-cooperative target does not have artificial feature markers. Therefore, contour features, including triangle supports of solar array, docking ring, and corner points of the spacecraft body, are used as the measuring features. To overcome the drawback of FOV limitation and imaging ambiguity of the camera, a "selfie stick" structure and a self-calibration strategy were implemented, ensuring that part of the contour features could be observed precisely when the two spacecraft approached each other. The observed features were constantly changing as the relative distance shortened. It was difficult to build a unified measurement model for different types of features, including points, line segments, and circle. Therefore, dual quaternion was implemented to model the relative dynamics and measuring features. With the consideration of state uncertainty of the target, a fuzzy adaptive strong tracking filter( FASTF) combining fuzzy logic adaptive controller (FLAC) with strong tracking filter(STF) was designed to robustly estimate the relative states between the servicing spacecraft and the target. Finally, the effectiveness of the strategy was verified by mathematical simulation. The achievement of this research provides a theoretical and technical foundation for future on-orbit servicing missions.

An efficient multi-relay selection scheme in cooperative communication system

Cooperative relaying has played an important role in rapid evolution of wireless communications.The cooperative performance strongly depends on the selected relays.In this paper,we concentrate on relay selection in amplify-and-forward(AF)cooperative communication system,and an optimal multi-relay selection scheme is put forward to minimize the average symbol error rate(SER)of the system.Firstly,for the minimum average SER,on the basis of the statistic channel information,we define a parameter named equivalent channel gain which describes the channel status of two phases in the cooperative process.Then,under the constraint of equal power allocation,an optimal relay selection scheme is proposed in ascending order of equivalent channel gain(ECG).The scheme implies that the suitable number of relay nodes should be selected under the different signal-to-noise ratio(SNR)ranges to minimize the average SER.Computer simulation results show that the average SER rate of the proposed scheme is lower than these of the other schemes.

基于MAS(Multi-AgentSystem)的多机器人系统:协作多机器人学发展的一个重要方向

机器人的应用方式正在由部件式单元应用向系统式应用方向发展 .这是实际应用的需要 ,也是技术发展的必然趋势 ;相关技术如计算机网络技术的发展也为它的实现提供了相应支持 .多机器人协作理论问题必然也已经成为机器人学研究的一个热点 ,其中 ,分布式人工智能 ( DAI)中的多智能体 (代理 )系统 ( MAS:Multi-agentSystem)理论已引起多机器人协作理论研究者的关注 .本文即在揭示协作多机器人系统与 MAS的内在联系的基础上 ,指出基于 MAS的协作多机器人系统是协作多机器人学发展的一个重要方向 .

基于Multi-Agent协作的井下机器人智能搜救系统

煤矿井下救援与逃生是煤矿安全生产中亟待解决的重大课题之一。发生矿难事故后,第一时间就是搜索并解救井下被困人员。传统的救援方式耗费大量的人力、物力和财力,且容易错过井下最佳救援的"黄金72小时"。通过建立基于Multi-Agent协作的煤矿井下智能搜救模型,设计出两类Agent模块,即SearchAgent和ContolAgent。利用Agent的主动性、自反应、自组织、自学习和协同沟通的特性,在矿难发生后,根据井下地图和多个SearchAgent反馈回来的路径信息进行汇总、分析与计算,精确筛选出最优、最近的搜救路线,并通知其他SearchAgent协同援助。应用多主体建模技术模拟井下救援路线,对于井下被困人员位置的定位、搜救方案的制定、救援人员的调度安排、物资的合理分配都具有十分重要的现实意义。

Multi-Agent系统中Agent知识获取的合作模型

Agent的知识是 Agent计算的前提 .在动态、不确定的 Multi- Agent系统中 ,Agent必须具备及时有效地获取所需知识的能力以求解问题 .现有的知识获取模型不能有效地支持在动态、不确定的 Multi- Agent系统中Agent对知识获取的要求 ,Agent的知识获取能力比较有限 .提出一个系统的、用于 Agent知识获取的合作模型KACM( knowledge- acquiring cooperation model)系列 ,包括被动模型、主动终止模型和主动非终止模型 .基于言语行为理论和以分枝时序逻辑为基础的形式化框架 ,讨论了 KACM所涉及的 Agent通信行为 ,分析了 Agent如何响应这些通信行为以完成知识交互 ,定义了各通信行为以及 KACM的满足语义 ,最后讨论了研究工作的意义 .