Effect of conformity on evolution of cooperation in a coordination game

Individual decision-making processes are not solely driven by self-interest maximization but are also influenced by the pressure to conform to the group.In primary games like the prisoner's dilemma,the presence of conformity pressure may facilitate the constructive development of cooperative behavior.In this study,we investigate how conformity influences the growth of cooperation in complicated coordination games.Our findings reveal that,even in the presence of stringent game rules,conformity can promote cooperation.In fact,a certain level of conformity pressure can even eliminate the“defection basin”of deer hunting games played on regular networks.Additionally,we demonstrate that the effect of conformity on cooperative behavior is contingent upon the degree of conformity pressure,with different levels of conformity pressure producing opposite effects.These findings provide novel insights into the promotion of cooperative evolution.For instance,if increasing the reward for cooperation has proven ineffective,manipulating the proportion of initial strategy choices may be a more promising approach.

Tibetan Plateau:Geodynamics and Environmental Evolution——The cooperative projects based upon the memorandum of CAS and DFG

The Tibetan Plateau （TP） plays a unique role in Earth System Sciences. It represents a key area to understand not only basic geodynamic processes linked with the formation and uplift of mountains and plateaus, but also the interaction between plateau uplift and environmental changes. Over the last 50 million years the formation of the TP has considerably influenced the global climate and monsoon system. Moreover, the TP proves to be extremely sensitive to present-day global change phenomena. Based upon the foundation of the new Institute of Tibetan Plateau Research （1TP） by the Chinese Academy of Sciences （CAS） and through the Memorandum signed by the CAS and DFG （Deutschen Forschungsgemeinschaft）, both CAS and DFG provide opportunities to intensify TP research and to develop coordinated research programs. ＂The Tibetan Plateau - Geodynamics and Environmental Evolution＂ consisting of one big projects funded by CAS and five projects funded by DFG that cover the pre- and early-collision history of the TP, the Palaeogene/Neogene uplift and climatic dynamics as well as the Late Quaternary and recent environmental and climatic changes on the TP. The projects are linked through several levels of interactions.

PSO Clustering Algorithm Based on Cooperative Evolution

Among the bio-inspired techniques,PSO-based clustering algorithms have received special attention. An improved method named Particle Swarm Optimization (PSO) clustering algorithm based on cooperative evolution with multi-populations was presented. It adopts cooperative evolutionary strategy with multi-populations to change the mode of traditional searching optimum solutions. It searches the local optimum and updates the whole best position (gBest) and local best position (pBest) ceaselessly. The gBest will be passed in all sub-populations. When the gBest meets the precision,the evolution will terminate. The whole clustering process is divided into two stages. The first stage uses the cooperative evolutionary PSO algorithm to search the initial clustering centers. The second stage uses the K-means algorithm. The experiment results demonstrate that this method can extract the correct number of clusters with good clustering quality compared with the results obtained from other clustering algorithms.

Dynamic aggregation evolution of competitive societies of cooperative and noncooperative agents

We propose an evolution model of cooperative agent and noncooperative agent aggregates to investigate the dynamic evolution behaviors of the system and the effects of the competing microscopic reactions on the dynamic evolution. In this model, each cooperative agent and noncooperative agent are endowed with integer values of cooperative spirits and nonco- operative spirits, respectively. The cooperative spirits of a cooperative agent aggregate and the noncooperative spirits of a noncooperative agent aggregate change via four competing microscopic reaction schemes： the win-win reaction between two cooperative agents, the lose-lose reaction between two noncooperative agents, the win-lose reaction between a coop- erative agent and a noncooperative agent （equivalent to the migration of spirits from cooperative agents to noncooperative agents）, and the cooperative agent catalyzed decline of noncooperative spirits. Based on the generalized Smoluchowski＇s rate equation approach, we investigate the dynamic evolution behaviors such as the total cooperative spirits of all coop- erative agents and the total noncooperative spirits of all noncooperative agents. The effects of the three main groups of competition on the dynamic evolution are revealed. These include： （i） the competition between the lose-lose reaction and the win-lose reaction, which gives rise to respectively the decrease and increase in the noncooperative agent spirits; （ii） the competition between the win-win reaction and the win-lose reaction, which gives rise to respectively the increase and decrease in the cooperative agent spirits; （iii） the competition between the win-lose reaction and the catalyzed-decline reaction, which gives rise to respectively the increase and decrease in the noncooperative agent spirits.

THE OPTIMAL CONTROL FOR PROMOTING THE COOPERATION IN EVOLUTION GAME GENERATED BY PRISONER'S DILEMMA

Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optimal control is designed for promoting cooperation based on the recent advances in mechanisms for the evolution of cooperation. Two con- trol strategies are proposed： compensation control strategy for the cooperator when playing against a defector and reward control strategy for cooperator when playing against a coop- erator. The feasibility and effectiveness of these control strategies for promoting cooperation in different stages are analyzed. The reward for cooperation can＇t prevent defection from being evolutionary stable strategy （ESS）. On the other hand, compensation for the coopera- tor can＇t prevent defection from emerging and sustaining. By considering the effect and the cost, an optimal control scheme with constraint on the admissible control set is put forward. By analyzing the special nonlinear system of replicator dynamics, the exact analytic solution of the optimal control scheme is obtained based on the maximum principle. Finally, the effectiveness of the proposed method is illustrated by examples.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

Zero-determinant strategy:An underway revolution in game theory

Repeated games describe situations where players interact with each other in a dynamic pattern and make decisions ac- cording to outcomes of previous stage games. Very recently, Press and Dyson have revealed a new class of zero-determinant （ZD） strategies for the repeated games, which can enforce a fixed linear relationship between expected payoffs of two play- ers, indicating that a smart player can control her unwitting co-player＇s payoff in a unilateral way [Proc. Acad. Natl. Sci. USA 109, 10409 （2012）]. The theory of ZD strategies provides a novel viewpoint to depict interactions among players, and fundamentally changes the research paradigm of game theory. In this brief survey, we first introduce the mathematical framework of ZD strategies, and review the properties and constrains of two specifications of ZD strategies, called pinning strategies and extortion strategies. Then we review some representative research progresses, including robustness analysis, cooperative ZD strategy analysis, and evolutionary stability analysis. Finally, we discuss some significant extensions to ZD strategies, including the multi-player ZD strategies, and ZD strategies under noise. Challenges in related research fields are also listed.

Rethinking quasispecies theory: From fittest type to cooperative consortia

Recent investigations surprisingly indicate that single RNA "stem-loops" operate solely by chemical laws that act without selective forces, and in contrast, self-ligated consortia of RNA stem-loops operate by biological selection. To understand consortial RNA selection, the concept of single quasi-species and its mutant spectra as drivers of RNA variation and evolution is rethought here. Instead, we evaluate the current RNA world scenario in which consortia of cooperating RNA stem-loops(not individuals) are the basic players. We thus redefine quasispecies as RNA quasispecies consortia(qs-c) and argue that it has essential behavioral motifs that are relevant to the inherent variation, evolution and diversity in biology. We propose that qs-c is an especially innovative force. We apply qs-c thinking to RNA stem-loops and evaluate how it yields altered bulges and loops in the stem-loop regions, not as errors, but as a natural capability to generate diversity. This basic competencenot error-opens a variety of combinatorial possibilities which may alter and create new biological interactions, identities and newly emerged self identity(immunity) functions. Thus RNA stem-loops typically operate as cooperative modules, like members of social groups. Fromsuch qs-c of stem-loop groups we can trace a variety of RNA secondary structures such as ribozymes, viroids, viruses, mobile genetic elements as abundant infection derived agents that provide the stem-loop societies of small and long non-coding RNAs.

Genetic-optimization framework for SVC transmission based on partial cooperative communication

A genetic-optimization framework based on the partial cooperation communication protocol is proposed for scalable video coding (SVC) stream transmission under multi-relay amplify and forward cooperative networks. Unlike traditional cooperative transmission schemes, the transmission mode for each coded unit in this new protocol can be switched flexibly between direct transmission and cooperative transmission. Obviously, under this protocol, the bandwidth efficiency and transmission robustness can be balanced adaptively according to the priority level of coded units and wireless channel fading characteristics. Based on this, a well-known genetic optimization algorithm-differential evolution is exploited here to find the jointly optimal transmission modes, power allocation and unequal error protection (UEP) channel coding strategies to minimize the end to end reconstructed video distortion. Extensive simulation results show that, compared with classical optimal cooperative UEP transmission schemes, the proposed optimized transmission framework based on the partial cooperative protocol can bring significant peak-signal-to-noise-ratio (PSNR) gains for the reconstructed video in a variety of channel bandwidth, power budget and test sequences.

Solving the Balance Problem of On-Line Role-Playing Games Using Evolutionary Algorithms

In on-line role-playing games (RPG), each race holds some attributes and skills. Each skill contains several abilities such as physical damage, hit rate, etc. Parts of the attributes and all the abilities are a function of the character’s level, which are called Ability-Increasing Functions (AIFs). A well-balanced on-line RPG is characterized by having a set of well-balanced AIFs. In this paper, we propose an evolutionary design method, including integration with an improved Probabilistic Incremental Program Evolution (PIPE) and a Cooperative Coevolutionary Algorithm (CCEA), for on-line RPGs to maintain the game balance. Moreover, we construct a simplest turn-based game model and perform a series of experiments based on it. The results indicate that the proposed method is able to obtain a set of well-balanced AIFs efficiently. They also show that in this case the CCEA outperforms the simple genetic algorithm, and that the capability of PIPE has been significantly improved through the improvement work.

Multi-robot mapping based on the adaptive differential evolution

Map building by multi-robot is very important to accomplish autonomous navigation,and one of the basic problems and research hotspots is how to merge the maps into a single one in the field of multi-robot map building.A novel approach is put forward based on adaptive differential evolution to map building for the multi-robot system.The multi-robot mapping-building system adopts the methods of decentralized exploration and concentrated mapping.The adaptive differential evolution algorithm is used to search in the space of possible transformation,and the iterative search is performed with the goal of maximizing overlapping regions.The map is translated and rotated so that the two maps can be overlapped and merged into a single global one successfully.This approach for map building can be realized without any knowledge of their relative positions.Experimental results show that the approach is effective and feasibile.

如何构建新型农业组织命运共同体:演进机制与知识基础——天虹丝绸纵向案例研究

如何构建新型农业组织命运共同体是能否有效推动农业现代化转型的关键问题。本文通过蚕丝制造企业翘楚——天虹丝绸的纵向案例研究,系统分析了该新型农业组织共同体的演进过程、合作机制与知识基础。研究主要有三点发现:第一,新型农业组织共同体的演进经历了从“利益共同体”到“事业共同体”再成为“命运共同体”的三个阶段,这一发现奠定了新型农业组织共同体演进的理论基础。第二,企业与农户、共育户、家庭农场主等核心利益相关方不同的合作机制推动了新型农业组织共同体的演化。意义建构机制推动命运共同体高级形态的跃升,是对从利益嵌入机制和关系渗透机制出发构建新型农业组织的一种补充和超越。第三,组织知识、产业知识和乡土知识的整合影响了合作机制构建与运行。此外厘清了新型农业组织命运共同体演进过程中的底层知识逻辑。研究为构建新型农业组织命运共同体以推动乡村振兴背景下传统农业的现代化转型与新质生产力的加快形成提供了路径选项与理论启发。

政企合作与过程选择——欠发达地区数字政府建设模式演化及政策效应

数字政府是“数字中国”的重要组成部分,在其中发挥了战略支撑作用,对欠发达地区数字政府的演化类型与政策效应进行研究对于实现共同富裕目标具有重要意义。通过文献分析、模型构建以及案例分析,对数字政府的动态演化进行分类,并以云南省“一部手机”系列建设为研究对象,通过合成控制法揭示欠发达地区数字政府政企合作建设模式的政策效应。结果表明:第一,政企合作是数字政府建设的重要支撑,基于政企合作视角建立数字政府动态演化矩阵,将数字政府建设分为学习型合作、高位驱动型合作、互补型合作、市场驱动型合作四种模式;第二,欠发达地区数字政府建设处于转型阶段,建设过程中呈现出政府侧权力减弱、市场侧权力增强的动态演化特点;第三,实证结果表明,高层主导的数字政府高位驱动型合作建设模式能够在欠发达地区数字政府建设初期取得相对显著的经济效应。

有人/无人机协同空战研究进展综述

有人/无人机协同空战是未来空战的重要发展方向,有人机和无人机协同运用、优势互补,形成灵活高效的作战体系,将对未来空战效能的提升发挥巨大作用。首先,阐述了近年来美军作战概念的发展演进,分析了美军有人/无人机协同作战的相关项目发展,提炼总结了有人/无人机协同空战的特点;其次,以穿透性制空作战为场景,分析了有人/无人机协同空战的具体运用和作战流程;最后,从航迹规划、空战决策、编队控制3个方面对有人/无人机协同空战的关键技术和研究现状进行梳理和分析,并对未来有人/无人机协同空战的研究发展方向进行了总结和展望。

汽车门板内饰多机器人焊接的动态协同规划

为了减小多机器人协同焊接的路径长度并提高机器人之间的负载均衡度,提出了基于动态规划-个体差异进化遗传算法的协同焊接规划方法。以多机器人协同焊接路径长度、负载均衡度为优化目标建立了优化模型,并分析了协同焊接约束条件。针对单机器人焊接路径规划问题,在遗传算法中针对染色体进化能力的差异性,提出了个体差异进化策略,给出了基于个体差异进化遗传算法的路径规划方法。针对多机器人协同焊接问题,使用动态规划将其划分为3个子问题,实现了多机器人协同焊接任务分配和路径规划。经某型汽车前门焊点路径规划验证,个体差异进化遗传算法规划的路径最佳长度、平均长度均优于传统遗传算法;经后门焊点的4机器人协同焊接验证,在满足无干涉约束下,这里方法的路径长度、负载均衡度优于文献[11]离散粒子群算法。实验验证了这里方法在多机器人协同焊接分配和规划问题中的优越性。

百廿年我国学前教育国际交流与合作的历史演进与展望

学前教育国际交流与合作是推动我国学前教育发展的重要动力。本研究基于口述史和文献资料,梳理我国学前教育国际交流与合作百廿年的演进历程,将其分为清末学前教育的早期引进与模仿、民国时期西方学前教育思想的学习与吸纳、中华人民共和国成立后的“全盘苏化”与对外交流的中断、改革开放后走向国际舞台以及全球化背景下的双向交流与经验输出五个阶段。研究发现,演进历程中的特点表现为从被动接受到主动交流、从局部交流到全面融入、从单一形式到多元合作以及从单向引进走向双向交流与经验输出。新时代背景下,我国学前教育国际交流与合作应注重讲好中国故事、立足中国传统文化与国情、积极开展国际学前教育研究与参与全球教育治理,并做好学前教育的对外援助与支持。

半双工译码转发中继信道下的空间耦合RA码设计

针对半双工译码转发中继信道,提出了一种可逼近三节点中继信道容量限的空间耦合RA码的设计方法。针对二进制删除信道,源节点分别向中继节点和目的节点发送空间耦合RA码,中继节点先正确恢复出源节点发送的空间耦合RA,然后再次编码产生额外的校验比特并转发给目的节点;目的节点结合中继节点发送的额外校验比特和源节点发送的空间耦合RA码进行译码,正确恢复出源节点的信息。为了评估所设计的空间耦合RA码在三节点中继信道下的渐近性能,推导了密度进化算法用于计算阈值。阈值分析结果表明,所提出的空间耦合RA码能够同时逼近源到中继链路和源到目的链路的容量限。同时,基于半双工二进制删除中继信道,仿真了所设计的空间耦合RA码的误码性能,结果表明,其误码性能与所推导的密度进化算法计算的阈值结果一致,呈现出逼近于容量限的优异性能,且优于采用空间耦合低密度奇偶校验(Low Density Parity Check,LDPC)码的性能。

赋形反射面天线的约束多目标优化设计研究

赋形反射面天线通常使用单目标优化算法进行设计,当期望波束特性具有多个相互冲突的目标和约束限制时,将无法确保输出最优解.为此,提出了该类天线的约束多目标优化方法 .基于有希望区域优化和自适应约束位移密度估计的思想,设计一种新型双种群协同进化约束多目标优化算法DPBE,在基准测试套件与其他3种主流算法的对比表明,该算法具备更强的全局寻优性与稳定性.将该算法应用于19~21 GHz单偏置抛物反射面天线的平顶波束赋形中,并与单目标优化算法IWO和多目标优化算法NSGA-II-DE在同型初始天线的不同优化模型下进行了性能对比,发现所提方法能在单次运行中满足所有约束条件并取得最佳结果 .

面向大规模重叠问题的两阶段差分分组方法

大规模重叠问题在实际工程应用中普遍存在,重叠问题子组间的共享变量给大规模重叠问题的优化带来了很大困难。基于分解的协同进化(CC)算法在解决大规模重叠问题上表现良好。然而,一些针对重叠问题设计的新型CC框架依赖问题分解方法获得重叠问题结构,而目前针对大规模重叠问题设计的分解方法不能同时兼顾高效性和准确性。为此,提出一种两阶段差分分组(TSDG)方法,在实现精确分组的同时显著减少了计算资源消耗。在第一阶段,采用基于有限差分原理的分组方法高效地识别子组集和共享变量集;第二阶段则提出一种分组改善方法检查前一阶段得到的子组集和共享变量集的信息,改正不准确的分组结果,以提高分组的稳定性和准确性。利用两阶段的协同作用,TSDG实现了对大规模重叠问题高效准确的分解。实验结果表明,TSDG能够在消耗较少计算资源的同时准确地分解大规模重叠问题。在优化实验中,TSDG在大规模重叠问题上的表现也优于对比算法。

乡村生活治理有效何以实现——以生活垃圾治理的积分制实践为例

推进乡村全面振兴背景下,以农村人居环境整治为核心的生活治理成为乡村治理的重点任务之一。村民合作是推动实现低成本高效能乡村生活治理的重要条件。以生活垃圾治理为例,基于田野调查发现,生活治理中的合作共治面临着激励难题,这一难题可在村庄生活共同体内社会竞争与社会声誉的基础上予以破解。生活治理过程中,地方治理主体实施积分兑换机制,通过评估村民的垃圾分类等行为并量化为积分,在此基础上进行不同层次的奖励。分级奖励机制有助于激发村庄中的社会竞争,使积分从对行动者的行为评估转化为道德评价。道德评价既是对垃圾分类过程中合作者的声誉奖励,也使不合作者面临声誉压力,进而发挥规范、惩戒的作用。这种声誉奖励和声誉压力可充分激发村民采取合作行为、约束不合作行为,进而提升乡村生活治理效能。