A Blind Spot in the Reframing of a Universe of Possibles: Towards a Suitable Model for Decision-Making Theory and A.I.

Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

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.

Cooperative Caching Strategy Based on Two-Layer Caching Model for Remote Sensing Satellite Networks

In Information Centric Networking(ICN)where content is the object of exchange,in-network caching is a unique functional feature with the ability to handle data storage and distribution in remote sensing satellite networks.Setting up cache space at any node enables users to access data nearby,thus relieving the processing pressure on the servers.However,the existing caching strategies still suffer from the lack of global planning of cache contents and low utilization of cache resources due to the lack of fine-grained division of cache contents.To address the issues mentioned,a cooperative caching strategy(CSTL)for remote sensing satellite networks based on a two-layer caching model is proposed.The two-layer caching model is constructed by setting up separate cache spaces in the satellite network and the ground station.Probabilistic caching of popular contents in the region at the ground station to reduce the access delay of users.A content classification method based on hierarchical division is proposed in the satellite network,and differential probabilistic caching is employed for different levels of content.The cached content is also dynamically adjusted by analyzing the subsequent changes in the popularity of the cached content.In the two-layer caching model,ground stations and satellite networks collaboratively cache to achieve global planning of cache contents,rationalize the utilization of cache resources,and reduce the propagation delay of remote sensing data.Simulation results show that the CSTL strategy not only has a high cache hit ratio compared with other caching strategies but also effectively reduces user request delay and server load,which satisfies the timeliness requirement of remote sensing data transmission.

Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

Bi-level model for shared parking decision-making based on parking lot assignment simulation

In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.

DECISION-MAKING OF SLICING SCHEME IN FUSED DEPOSITION MODELING PROCESS BASED ON ANALYTICAL HIERARCHICAL PROCESS

Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.

Joint inversion of gravity and magnetic data for a two-layer model

Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.

Asymptotic solution of a weak nonlinear model for the mid-latitude stationary wind field of a two-layer barotropic ocean

A weak nonlinear model of a two-layer barotropic ocean with Rayleigh dissipation is built.The analytic asymptotic solution is derived in the mid-latitude stationary wind field,and the physical meaning of the corresponding problem is discussed.

A Decision-Making Framework Model of Cutting Fluid Selection for Green Manufacturing and the Case Study

Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

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.

Effect of the Coefficient on the Performance of A Two-Layer Boussinesq- Type Model

The coefficients embodied in a Boussinesq-type model are very important since they are determined to optimize the linear and nonlinear properties.In most conventional Boussinesq-type models,these coefficients are assigned the specific values.As for the multi-layer Boussinesq-type models with the inclusion of the vertical velocity,however,the effect of the different values of these coefficients on linear and nonlinear performances has never been investigated yet.The present study focuses on a two-layer Boussinesq-type model with the highest spatial derivatives being 2 and theoretically and numerically examines the effect of the coefficient on model performance.Theoretical analysis show that different values for(0.13≤α≤0.25)do not have great effects on the high accuracy of the linear shoaling,linear phase celerity and even third-order nonlinearity for water depth range of 0<kh≤10(k is wave number and h is water depth).The corresponding errors using different values are restricted within 0.1%,0.1%and 1%for the linear shoaling amplitude,dispersion and nonlinear harmonics,respectively.Numerical tests including regular wave shoaling over mildly varying slope from deep to shallow water,regular wave propagation over submerged bar,bichromatic wave group and focusing wave propagation over deep water are conducted.The comparison between numerical results using different values of,experimental data and analytical solutions confirm the theoretical analysis.The flexibility and consistency of the two-layer Boussinesq-type model is therefore demonstrated theoretically and numerically.

Shared Decision-Making after Implementation of the Chronic Care Model (CCM)—An Evaluative Approach

Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the Electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi time points and multi indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the Multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

Two-Layer Non-Hydrostatic Model for Generation and Propagation of Interfacial Waves

When pycnocline thickness of ocean density is relatively small, density stratification can be well represented as a two-layer system. In this article, a depth integrated model of the two-layer fluid with constant density is considered,and a variant of the edge-based non-hydrostatic numerical scheme is formulated. The resulting scheme is very efficient since it resolves the vertical fluid depth only in two layers. Despite using just two layers, the numerical dispersion is shown to agree with the analytical dispersion curves over a wide range of kd, where k is the wave number and d the water depth. The scheme was tested by simulating an interfacial solitary wave propagating over a flat bottom, as well as over a bottom step. On a laboratory scale, the formation of an interfacial wave is simulated,which also shows the interaction of wave with a triangular bathymetry. Then, a case study using the Lombok Strait topography is discussed, and the results show the development of an interfacial wave due to a strong current passing through a sill.

A decision-making model of gear process for green manufacturing

A decision-making model of gear process for green manufacturing is presented, which integrates the five objectives including the time, quality, cost, resource consumption and environmental impact of gear process together into the development of a strategy. Mathematical description is provided for the multi-objectives decision-making model. The expert judgment and the multi-fuzzy assessment theory are introduced to do sensible comparisons and give quantitative results. A case study on practical cutting tool selection in gear machining demonstrates that the proposed model is applicable.

Decision-Making Model of Public Service Facility Configuration in Multi-agent Communities and Its Application

The decision.making process of the public service facility configuration in multi.agent community is usually simplistic and static. In order to reflect dynamic changes and interactions of all behavior subjects induding of residents, real estate developers and the government, a decision-making model of public service facility configuration according to the multi-agent theory was made to improve the efficiency of the public service facility configuration in community and the living quality of residents. Taking a community to the cast of Jinhui Port in Fengxian District in Shanghai for example, the model analyzed the decision-makers＇ adaptive behaviors and simulated the decision.making criteria. The results indicate that the decision-making model and criteria can be well of satisfying the purpose of improving validity and rationality of public service facility configuration in large community.

Toward Modelling of Transformational Change Processes in Farm Decision-Making

In the coming decades, agricultural systems will have to adapt to tremendous challenges. Behavioral models have important potential to better understand and steer changes toward sustainability brought about by this context. Relying on a literature review, we distinguish incremental changes (extensions of what is already done) and transformational changes, which involve the reorientation of a considerable amount of farming activities. Transformational changes are particularly important in the context of global change. Existing integrated modelling frameworks based on behavioral theories are suited for incremental changes, but remain limited for transformational changes. Qualitative studies provide important insights on two key aspects of transformational changes, learning and social relations, but they have not been explicitly oriented toward computer modelling yet. Based on this literature and three seminal decision-making approaches, we propose a description of transformational change processes in farm decision-making, as a first step toward an implementation in agent-based models.