Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment

The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment.It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players,as well as the impact of participants’manipulative behaviors on the state changes of the players.A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario.Subsequently,the strategy selection interaction relationship,strategy evolution stability,and dynamic decision-making process of the game players are investigated and verified by simulation experiments.The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent’s strategies.Especially in a highly uncertain environment,even small information asymmetry or miscalculation may have a significant impact on decision-making.This also confirms the feasibility and effectiveness of the method proposed in the paper,which can better explain the behavioral decision-making process of the agent in the interaction process.This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model.

On the role of impulsivity and decision-making in suicidal behavior

Suicide risk constitutes a complex set of interacting demographic, clinical, psychobiological and environmental variables. Impulsivity is a long-known risk factor for suicide attempts. However, research based on clearer conceptual refinement in this area is imperative. One emerging field of study is that of decision-making. Impulsivity involves a failure of higher-order control, including decision-making. Using standardized operational definitions that take into consideration relevant aspects of impulsivity, including state- and trait-components and a deeper understanding of the process of decision-making in the suicidal mind, we may come a step closer to understanding suicidality and winning the fight in this scourge of human suffering.

Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study

Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions.

Unlocking the Network Traffic Password of the Sudden Popularity of Oriental Selection:Consumer Behavior Decision-Making Mechanism Based on Mental Accounting Theory

This paper explores the decision-making mechanism of the consuming behavior hidden behind the sudden popularity of the Oriental Selection Company in terms of the mental accounting theory.Firstly,according to the“Non-alternative”characteristics of mental accounting,this paper expounds how the strategy of the bilingual live-streaming of Oriental Selection promoters stimulates consumers’desire to buy the advertised products and services whilst using the utility theory of mental accounting to analyze how Oriental Selection promoters improve consumers’acquisition utility and total utility.Secondly,we sum up the successful experiences of Oriental Selection:The live-streaming industry should apply the theory of mental accounting in effectively overcoming the shortcomings of the live-streamed marketing by stimulating consumers’desire and influencing their decision-making behavior through the streaming of content that triggers them to make purchases.This is achievable by abandoning the traditional ways of loudly urging consumers to buy goods.Finally,this paper puts forward some suggestions on how to use the mental accounting theory in promoting sustainable consumption and points out the prospects for Oriental Selection.

Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships:A Hybrid Method and Benefit Distribution Study

Public-private partnerships(PPPs)have been used by governments around the world to procure and construct infrastructural amenities.It relies on private sector expertise and funding to achieve this lofty objective.However,given the uncertainties of project management,transparency,accountability,and expropriation,this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally.Interestingly,the reasonable benefit distribution scheme in a PPP project is related to the behavior decisionmaking of the government and social capital,aswell as the performance of the project.In this paper,the government and social capital which are the key stakeholders of PPP projects were selected as the research objects.Based on the fuzzy expected value model and game theory,a hybrid method was adopted in this research taking into account the different risk preferences of both public entities and private parties under the fuzzy demand environment.To alleviate the problem of insufficient utilization of social capital in a PPP project,this paper seeks to grasp the relationship that exists between the benefit distribution of stakeholders,their behavioral decision-making,and project performance,given that they impact the performance of both public entities and private parties,as well as assist in maximizing the overall utility of the project.Furthermore,four game models were constructed in this study,while the expected value and opportunity-constrained programming model for optimal decision-making were derived using alternate perspectives of both centralized decision-making and decentralized decision-making.Afterward,the optimal behavioral decision-making of public entities and private parties in four scenarios was discussed and thereafter compared,which led to an ensuing discussion on the benefit distribution system under centralized decision-making.Lastly,based on an example case,the influence of different confidence levels,price,and fuzzy uncertainties of PPP projects on the equilibrium strategy results of both parties were discussed,giving credence to the effectiveness of the hybrid method.The results indicate that adjusting different confidence levels yields different equilibriumpoints,and therefore signposts that social capital has a fair perception of opportunities,as well as identifies reciprocal preferences.Nevertheless,we find that an increase in the cost coefficient of the government and social capital does not inhibit the effort of both parties.Our results also indicate that a reasonable benefit distribution of PPP projects can assist them in realizing optimum Pareto improvements over time.The results provide us with very useful strategies and recommendations to improve the overall performance of PPP projects in China.

Analysis of Influencing Factors Tourists1 Purchase Decision-making Behavior in Kunming

Based on the theory of consumer behavior,this paper analyzes the current situation of tourism shopping market in Kunming,and analyzes the decision-making behavior of tourists shopping in Kunming with the questionnaire survey,and clarifies the influencing factors of the decision-making behavior of visitors to Kunming.In the future,the influencing factors of Kunming tourists'shopping decision-making behavior are combined with the current situation of Kunming's tourism shopping market.The problems of cheating-induced shopping,the high price of shopping products,the low level of tourism shopping experience and the imperfect after-sales service are analyzed.Finally,the corresponding countermeasures and suggestions are proposed from four aspects:rectifying the tourism shopping market,establishing a sound price supervision mechanism,strengthening the tourism shopping experience,and improving after-sales service.

Study on Tourism Decision-making Pattern of European Tourists in China——With European Tourists in Xi’an City as a Study Case

With the inbound tourism market data supported by National Natural Science Foundation of China as the basis, this study through researching the tourism decision-making behaviors of inbound tourists, adopting questionnaire survey among European tourists in Xi'an City, analyzed their tourism decision behaviors and influencing factors, and aimed to propose pertinent suggestions for the expansion of European tourist market for Xi'an City.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

Human-Like Decision-Making of Autonomous Vehicles in Dynamic Traffic Scenarios

With the maturation of autonomous driving technology, the use of autonomous vehicles in a socially acceptable manner has become a growing demand of the public. Human-like autonomous driving is expected due to the impact of the differences between autonomous vehicles and human drivers on safety.Although human-like decision-making has become a research hotspot, a unified theory has not yet been formed, and there are significant differences in the implementation and performance of existing methods. This paper provides a comprehensive overview of human-like decision-making for autonomous vehicles. The following issues are discussed: 1) The intelligence level of most autonomous driving decision-making algorithms;2) The driving datasets and simulation platforms for testing and verifying human-like decision-making;3) The evaluation metrics of human-likeness;personalized driving;the application of decisionmaking in real traffic scenarios;and 4) The potential research direction of human-like driving. These research results are significant for creating interpretable human-like driving models and applying them in dynamic traffic scenarios. In the future, the combination of intuitive logical reasoning and hierarchical structure will be an important topic for further research. It is expected to meet the needs of human-like driving.

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

This paper is to explore the problems of intelligent connected vehicles(ICVs)autonomous driving decision-making under a 5G-V2X structured road environment.Through literature review and interviews with autonomous driving practitioners,this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system.Secondly,situated on this framework,it builds a hierarchical finite state machine(HFSM)model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method(EWM)and analytic hierarchy process method(AHP)and by employing a model fusion approach between the technique for order preference by similarity to an ideal solution(TOPSIS)and grey relational analysis(GRA).The HFSM model is composed of two layers:the global FSM model and the local FSM model.The decision of the former acts as partial input information of the latter and the result of the latter is sent forward to the local pathplanning module,meanwhile pulsating feedback to the former as real-time refresh data.To identify different traffic scenarios in a cerebrum-like way,the global FSM model is designed as 7 driving behavior states and 17 driving characteristic events,and the local FSM model is designed as 16 states and 8 characteristic events.In respect to designing a cerebrum-like algorithm for state transition,this paper firstly fuses AHP weight and EWM weight at their output layer to generate a synthetic weight coefficient for each characteristic event;then,it further fuses TOPSIS method and GRA method at the model building layer to obtain the implementable order of state transition.To verify the feasibility,reliability,and safety of theHFSMmodel aswell as its TOPSISGRA state transition algorithm,this paper elaborates on a series of simulative experiments conducted on the PreScan8.50 platform.The results display that the accuracy of obstacle detection gets 98%,lane line prediction is beyond 70 m,the speed of collision avoidance is higher than 45 km/h,the distance of collision avoidance is less than 5 m,path planning time for obstacle avoidance is averagely less than 50 ms,and brake deceleration is controlled under 6 m/s2.These technical indexes support that the driving states set and characteristic events set for the HFSM model as well as its TOPSIS-GRA algorithm may bring about cerebrum-like decision-making effectiveness for ICV autonomous driving under 5G-V2X intelligent road infrastructure.

A Theoretical Approach to the Effective Decision-Making Process

This research develops and elaborates studies done for a contribution to the 2019 PIC International Conference 2019 in Malta, about the decision-making process. Decision-making is the act of choosing between two or more courses of action. In the wider process of problem-solving, decision-making involves choosing between possible solutions to a problem, and these decisions can be made through either an intuitive or reasoned process, or a combination of the two. The study of decision-making processes, to be understood as the role of human factors, becomes particularly interesting in complex organizations. This research aims to analyze how an effective team, within organizations, can develop a more correct and effective decision-making, in order to get an optimal solution, overcoming the typical uncertainty. The paper describes the point of departure of decision in complex, time-pressured, uncertain, ambiguous and changing environments. The use of a leading case (the Tenerife air accident, 1977), will lead us to the desired results, i.e. to demonstrate how an effective decisional process, including team dynamics, can be useful to reduce the risk, present in all decisions, and reduce errors. The case of Tenerife air disaster, confirm our research. In that case, in fact, the group dynamics prove not to have worked. Thus, we can state that if a team approach had been followed instead of a more individual one, the results would probably have been different. The central belief of the research, is that classic decision theory could benefit from a team approach, which reduces the risk that a decision may lead to undesirable consequences. As demonstrated with the case study, within organizations, the decision-making is not a solitary action. Decisions, in fact, are made within a team and in order to be able to function effectively in a group, and manage group situations, there are essential skills. The team can then become a resource for the decisional process and problem solving, but it is necessary to understand the dynamics.

Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance

With the development of intelligent vehicles and autonomous driving technology,the safety of vulnerable road user(VRU)in traffic has been more guaranteed,and many research achievements have been made in the key area of collision avoidance decision-making methods.In this paper,the knowledge mapping method is used to mine the available literature in depth,and it is found that the research focus has shifted from the traditional accident cause analysis to emerging deep learning and virtual reality technology.This paper summarizes research on the three core dimensions of environmental perception,behavior cognition and collision avoidance decision-making in intelligent vehicle systems.In terms of perception,accurate identification of pedestrians and cyclists in complex environments is a major demand for VRU perception;in terms of behavior cognition,the coupling of VRU intention identification and motion trajectory prediction and other multiple factors needs further research;in terms of decision-making,the intention identification and trajectory prediction of collision objects are not included in the risk assessment model,and there is a lack of exploration specifically for cyclists'collision risk.On this basis,this paper provides guidance for the improvement of traffic safety of contemporary VRU under the conditions of intelligent and connected transportation.

Increased physical activity, physician recommendation, and senior center participation

Physical activity is a recognized preventive health measure for seniors and an important focus for senior centers. This paper employs the Andersen Behavioral Model to explore increased physical activity and participation in three types of senior center activities: physical fitness, dance/aerobic classes, and chair exercises. Data were collected in 2006 on 798 and in 2007 on 742 participants at 21 multipurpose senior centers in a large urban county. Logistic regression analysis (PROC RLOGIST in SAS-callable SUDAAN) was employed to predict increased physical activity, with modes of center participation in physical activity as mediating factors. Predisposing and enabling factors predicted both engaging in center-based exercise programs and increases in physical activity;but the strongest predictors of increases in physical activity were needed factors: physician recommendations to increase exercise and to lose weight. Implications are that both SCs and healthcare providers are important to promote physical activity in the older population.

Underrecognition and un-dertreatment of stress-related psychiatric disorders in physicians:Determinants,challenges,and the impact of the COVID-19 pandemic

Medical practitioners’duties are highly stressful and performed in a particularly challenging and competitive work environment.Stress and burnout among physicians have emerged as a worldwide public health problem in recent years.A high level of distress and burnout can lead to clinically significant behavioral health problems,such as stress-related psychiatric disorders.Mounting evidence shows that physicians have higher risks of insomnia,anxiety,and depression than the general population,especially during the coronavirus disease 2019 pandemic.However,the behavioral health problems of these vulnerable healthcare professionals are noteworthy for being underrecognized and undertreated.In this minireview,we summarize the current progress of studies on the prevalence and determinants of distress and stress-related psychiatric disorders among physicians and their healthcare-seeking behaviors.We discuss future research directions and the clinical approach that may maximize self-awareness and promote prompt and adequate treatment for clinically significant behavioral health problems of physicians.

The Comparative Role of Intervening Variables in Understanding Farmers＇ Adoption Behavior

The purpose of this study was to indentify the most important determinants associated with behavior change by comparing the influence of intervening variables and the characteristics of the farmer and the farm （independent variables） on the adoption behavior of farmers for recommended agronomic practices. A total of 107 farmers out of a population of 214 were randomly selected from two adjoining districts of South Africa and Lesotho. Chi-square and correlations and regression analyses were used to determine the relationship between the independent, dependent and intervening variables. The results show clear differences between the independent in regard to their influence on adoption behavior, but these influences also vary significantly between the practices. In general the influence of independent variable is limited, and together their total contribution in explaining the variance in adoption （R2） varied between about 20 to 40 percent whilst that of the intervening variables varied between 50 and over 70 percent, which clearly supports the research hypothesis that their prediction arid explanation value in terms of behavior is much bigger than that of independent, personal and environmental factors.

松散型医联体优质医疗资源下沉驱动机制探究——微观合作理论视角下的定性比较分析

目的:旨在探究并激发松散型医联体中作为优质医疗资源的核心医院医生主动下沉基层并持续参与合作的路径机制,为提升医联体合作效能提供有益参考。方法:采用fsQCA的方法,运用微观层面的合作关系承诺理论、合作动机理论、社会交换理论与合作强化理论,对B市X区松散型医联体核心医院205位医生进行调查。结果:医联体核心医院医生主动下沉参与合作的关系承诺水平受到医生对合作的工作意义感知、机会成本感知、组织支持以及团队合作经历等多因素的影响,形成了合并驱动效应、经验强化效应、利他触发效应等三种并发驱动机制路径。其中,工作意义感知是必要条件,合作经历对医生持续参与有重要作用。结论:医生下沉参与合作的关系承诺水平受到多种因素组合的驱动,不同路径的激励机制在松散型医联体内具有异质性。针对具体情境设计适宜的激励和支持策略,可有效驱动松散型医联体核心医院优质医疗资源的主动下沉。

基于CiteSpace的国内在线医疗用户择医行为研究

目的:探究在线医疗用户择医行为的研究热点及演化脉络,为推动在线医疗用户择医行为研究的发展提供理论指导。方法:基于中国知网2016-2023年以“在线择医”“在线问诊”为主题的文献,运用CiteSpace软件,就在线医疗用户择医行为研究进展、共现网络和关键词进行知识图谱分析。结果:在线医疗用户择医行为相关研究总体呈现上升趋势;高校管理学院是在线医疗用户择医行为研究的主要力量,但尚未形成稳定的核心作者群,相关合作研究尚局限在机构内部;高频关键词有“患者选择”“医生推荐”等。结论:需加强跨学科研究,加强学者及机构间合作,还需根据政策变化拓展在线医疗用户择医行为研究前沿;患者应考量海量信息,做出理性决策;医生应提升综合素质,提供高质量服务;在线医疗平台应优化系统设计,提升用户体验。

医保支付与医生薪酬的激励转化机制研究——DRG付费下的实验研究证据

目的:探究与DRG支付方式改革相适应的医生薪酬激励设计,为优化医保支付方式改革相关政策提供参考依据。方法:利用经济学实验,设计七种将DRG支付激励转化为薪酬激励的医生薪酬支付方式,招募210名医学生和65名医生作为被试人员,测试其在不同薪酬激励下为患者提供的医疗服务数量及相应患者健康效益。结果:向医生反馈DRG支付情况或将DRG支付结余与医生绩效工资挂钩均会将支付方式的激励传导给服务提供者,在此基础上,引入以质量为基础的按绩效支付,被试者提供的服务量与最优服务量之间的差值减小,患者健康效益损失比也降低。结论:在将DRG支付激励传导给服务提供者时,与以质量为基础的按绩效支付相结合的医生薪酬设计更有利于提高患者健康效益。

基于实验经济学方法的不同支付方式对医生决策行为影响研究

目的探索医生在不同医保支付方式下及面对不同健康状况患者时提供医疗服务行为的变化。方法招募110名医学院校学生作为被试者,通过实验经济学方法模拟医生进行医疗行为决策场景。结果被试者在按服务项目支付(fee-for-service,FFS)中为每名患者提供的医疗服务平均数量高于按人头支付(capitation payment,CAP);被试者在混合支付方式下提供的服务数情况优于单一支付方式;FFS系统中对重症患者的最优决策比例最高,而在CAP系统中对轻症和重症患者作出的最优决策数差异无统计学意义(P>0.05);不同支付方式、医生利润及患者健康状况对被试者提供的最优决策存在影响。结论在FFS系统中,轻症患者接受了更多的过度医疗服务;在CAP系统中,中症和重症患者治疗不足的情况更严重;混合支付方式能够一定程度克服单一支付方式的弊端,发挥综合优势。被试者在提供医疗行为的过程中存在利他异质性,可以通过改变外部客观条件和优化内生性因素对医生决策行为进行干预。