Dynamic Pricing Model of E-Commerce Platforms Based on Deep Reinforcement Learning

With the continuous development of artificial intelligence technology,its application field has gradually expanded.To further apply the deep reinforcement learning technology to the field of dynamic pricing,we build an intelligent dynamic pricing system,introduce the reinforcement learning technology related to dynamic pricing,and introduce existing research on the number of suppliers(single supplier and multiple suppliers),environmental models,and selection algorithms.A two-period dynamic pricing game model is designed to assess the optimal pricing strategy for e-commerce platforms under two market conditions and two consumer participation conditions.The first step is to analyze the pricing strategies of e-commerce platforms in mature markets,analyze the optimal pricing and profits of various enterprises under different strategy combinations,compare different market equilibriums and solve the Nash equilibrium.Then,assuming that all consumers are naive in the market,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.By comparing and analyzing the optimal pricing and total profit of each enterprise under different strategy combinations,the subgame refined Nash equilibrium is solved.Finally,assuming that the market includes all experienced consumers,the pricing strategy of the duopoly e-commerce platform in emerging markets is analyzed.

Chaos game representation walk model for the protein sequences

A new chaos game representation of protein sequences based on the detailed hydrophobic-hydrophilic （HP） model has been proposed by Yu et al （Physica A 337（2004） 171）. A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CCR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA（p, d, q） model is introduced into the protein sequence analysis. This model is applied to simulating real CCR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA（p, d, q） model.

Multi-Modal Data Analysis Based Game Player Experience Modeling Using LSTM-DNN

Game player modeling is a paradigm of computational models to exploit players’behavior and experience using game and player analytics.Player modeling refers to descriptions of players based on frameworks of data derived from the interaction of a player’s behavior within the game as well as the player’s experience with the game.Player behavior focuses on dynamic and static information gathered at the time of gameplay.Player experience concerns the association of the human player during gameplay,which is based on cognitive and affective physiological measurements collected from sensors mounted on the player’s body or in the player’s surroundings.In this paper,player experience modeling is studied based on the board puzzle game“Candy Crush Saga”using cognitive data of players accessed by physiological and peripheral devices.Long Short-Term Memory-based Deep Neural Network(LSTM-DNN)is used to predict players’effective states in terms of valence,arousal,dominance,and liking by employing the concept of transfer learning.Transfer learning focuses on gaining knowledge while solving one problem and using the same knowledge to solve different but related problems.The homogeneous transfer learning approach has not been implemented in the game domain before,and this novel study opens a new research area for the game industry where the main challenge is predicting the significance of innovative games for entertainment and players’engagement.Relevant not only from a player’s point of view,it is also a benchmark study for game developers who have been facing problems of“cold start”for innovative games that strengthen the game industrial economy.

System dynamics of behaviour-evolutionary mix-game models

In real financial markets there are two kinds of traders： one is fundamentalist, and the other is a trend-follower. The mix-game model is proposed to mimic such phenomena. In a mix-game model there are two groups of agents： Group 1 plays the majority game and Group 2 plays the minority game. In this paper, we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents： if the winning rates of agents are smaller than a threshold, they will join the other group; and agents will repeat such an evolution at certain time intervals. Through the simulations, we obtain the following findings： （i） the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents; （ii） the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours; （iii） there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution; （iv） parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.

Hysteresis behavior and nonequilibrium phase transition in a one-dimensional evolutionary game model

We investigate a simple evolutionary game model in one dimension. It is found that the system exhibits a discontinuous phase transition from a defection state to a cooperation state when the b payoff of a defector exploiting a cooperator is small. Furthermore, if b is large enough, then the system exhibits two continuous phase transitions between two absorbing states and a coexistence state of cooperation and defection, respectively. The tri-critical point is roughly estimated. Moreover, it is found that the critical behavior of the continuous phase transition with an absorbing state is in the directed percolation universality class.

Game Modeling and Strategic Behavior Analysis in Public Goods Provision： Evidence From Water Resources Management

The utility of public goods vary with the behaviors of stakeholders （players）, and it is appropriate to study effective supply and management of public goods with game modeling and analysis. The comparison effect is the key issue of public good provision both in theoretical analysis and in practice. One major contribution of the paper is the extension of Clarke-Groves mechanism, to achieve which strategic behavior analysis is applied through the analysis and the comparison effect among various stakeholders in different stages is created and highly emphasized. In the first section of this paper, the definition of integrated water resources management （IWRM）, the importance of stakeholder participation as well as some models and methods that have been applied are illustrated. Following this, the framework of analysis is elaborated, in which the scenario and aims are shown, and it is claimed that game theory is the main approach, which includes both cooperative games and non-cooperative games. To achieve the aims of the public project, five approaches from game theory are able to cover the entire process of the project, and the fourth approach on interest compensation mechanism is the highlight of the research. After this, the interest compensation mechanism is demonstrated in the model section, and is proved to be an incentive compatible mechanism that makes each stakeholder choose to behave in accordance with the interest of the entire project. The Clarke-Groves mechanism is applied and extended in establishing the model, and the utility change by the comparison among stakeholders （defined as the comparison effect） is involved. In the application section, a water project is analyzed in consideration of various stakeholders, and other possible applications are also indicated.

Urban Configuration Analysis of Idle Land Market Based on Game Model

In recent years, the speed of urban development becomes faster and faster with expanding of land construction scale, and a lot of idle lands lead to serious land waste. This paper builds game model by carrying out a market allocation analysis and applying economic game theory to the analysis of current idle land problem; it gets six kinds of results through analyzing the game model of idle land market, and the final Nash equilibrium is(system innovation, publicly traded) through contrastive to help balance the game relationship between government and the user of idle land and raise some new scientific and rational institutions to serve as future references for effective usage of idle land.

Research on Financing Game Model of Small and Medium-sized Enterprises based on Different Risk Categories

With the development of market economy and the deepening of economic system reform, some of the Small and medium-sized（SME） enterprises have become the most dynamic economic growth point in the national economy. Nevertheless, SMEs are facing a lot of problems in the market competition, such as technical backwardness, information lag, lack of talents, etc.. The healthy development of SMEs is very important, whereas, SMEs’ financing is a worldwide problem, and the result of financing game between banks and enterprises depends on a variety of decision-making factors. In this paper, from the point of view of bank, we analyze the diffi culties of external financing of SMEs, and establish a financing game model based on different risk categories, in order to better solve the problems that remain in the process of financing and promote the healthy and sustainable development of SMEs.

Application of fuzzy optimization model in the evaluationof urban flood-waterloggedvulnerabilitybased on the synthetic weight ofgame theory

The evaluation of urban flood-waterlogged vulnerability is very important to the safety of urban flood control. In this paper, the evaluation of consolidated index is used. Respectively, AHP and entropy method calculate the subjective and objective weight of the evaluation indicators, and combine them by game theory. So we can obtain synthetic weight based on objective and subjective weights. The evaluation of urban flood-waterlogged vulnerability as target layer, a single variable multi-objective fuzzy optimization model is established. We use the model to evaluate flood-waterlogged vulnerability of 13 prefecture-level city in Hunan, and compare it with other evaluation method. The results show that the evaluation method has certain adaptability and reliability, and it＇ s helpfid to the construction planning of urban flood control.

Spatial restructuring and the logic of industrial land redevelopment in urban China: Ⅳ. A case study of jointly redevelopment by multi-actors

Within the inventory era, urban shrinkage characterized by economic decline and space decay has been widely witnessed in China. The modes and trajectories of urban redevelopment have thus become areas of major concern for both policymakers and scholars. Taking the multi-actor participation nature of redevelopment, this paper stemming from the game-theoretical approach demonstrates in empirical terms on two major fronts. First, the redevelopment of industrial land without the transfer of land use right is shown to be deadlocked by the incapacitation of the original land-user and unlocked with the participation of the new developer. Second, the preference of the original land-user to maximize its interests by operating by itself rather than continue to cooperate with the new developer is observed in the post-redevelopment stage. Therein, the entrepreneurial local government acts only as a “mediator” between the two market entities and tends not to directly intervene in their cooperation. Thus that, it is the reasonable distribution of potential benefits or the pricing of different rights in the land property right bundle rather than their definition that matters more for land redevelopment. Because the delineation of land property rights has never been a problem in a mature land market, particularly for stock industrial land.

Game theory approach to optimal capital cost allocation in pollution control

This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.

Game Analysis and Countermeasures on Increasing Prices of Agricultural Products under Triple Supply Chain

From the perspective of supply chain of agricultural products,by establishing Stackelberg game model based on triple supply chain,this paper researches the price formation and profit distribution mechanism of agricultural products under circumstance of non-cooperation and cooperation.The results show the main factors responsible for the hiking of prices of agricultural products as follows:the cost of agricultural products climbs incessantly;the circulation cost hovers at high level;the factor inputs of agricultural products are short;inflation pressure is incessantly mounting;the profit distribution of supply chain is irrational.Finally,corresponding countermeasures are put forward.

Early-warning signals for an outbreak of the influenza pandemic

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CCR wall〈 sequences for the pandemic years （or ＋ -1 to 2 years） are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.

Evaluation of global navigation satellite system spoofing efficacy

The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.

Agile Scheduling for MES in a Complex Information Environment

Since Manufacturing Execution System (MES) is a bridge which links the upper planning system of the enterprise and the control system of the shop floor, various kinds of the information with different characteristics flow through the system. The information environment of MES and its effect on MES scheduling are analyzed. A methodological proposal is given to address the problem of agile scheduling in a complex information environment, based on which a microeconomic market and game theoretic model-based scheduling approach is presented. The future development of this method is also discussed.

Research on the Effects of the Most Used Market Power Mitigation Mechanisms Considering Different Market Environments

The market power mitigation method of the supply-side has become one of the key points affecting the stability of the electricity spot market.Different mitigation mechanisms are used in the current mature electricity markets of the world.However,the same market power mitigation mechanism shows different effects in different market environments.Every market operator in the world needs the most efficient way to mitigate market power.Considering that there is no relevant literature discussing the market power effects of different mitigation methods in detail,the mitigation effects need to be discussed and further researched.So,we analyze the effects of the most utilized market power mitigation mechanisms while considering different market environments.Firstly,we establish a Nash-Stackelberg interactive game model to simulate the competitive strategies of power suppliers.Secondly,the different market power mitigation approaches are modeled.Then,a multi-agent system(MAS)genetic interior-point algorithm is proposed to solve the problem of suppliers.Finally,through the simulation analysis,the market power mitigation effects of different mechanisms while considering three operation states of the system in two market structures are all analyzed.

Research on Regulating and Controlling Homogenization of Entertainment Programs--Based on Game Theory

With the prevailing and popular entertainment programs, it brought huge benefits to TV stations, but at the same time caused a variety problems of homogenization. The paper analyzes the causes of the entertainment programs, the root of homogenization, building game theory models between TV stations, TV station and audience to regulate and control the issue of homogeneity about entertainment programs.

Analysis of Drug Purchase and Pricing Decision under the Mode of Procurement with Target Quantity

Objective To study the reasonable pricing strategy to effectively reduce the risk of drug supply disruption.This paper studies the vertical competition between drug purchasers and pharmaceutical enterprises,and the horizontal competition between different pharmaceutical enterprises.Based on the wholesale price of drugs made by pharmaceutical enterprises,drug purchasers adopt different procurement strategies.Methods A multi-stage game model was used to analyze the collusion and competition between two drug procurement parties.Results and Conclusion(1)Enterprise B can choose the optimal game strategies according to the stability of enterprise A;(2)Two procurement parties should choose collusion when the risk of supply interruption is low;(3)Emergency dual sourcing strategy is better than single sourcing strategy;(4)The optimal procurement quantity is irrelevant to the monotonicity of the stability of enterprise A in Cournot game.Through numerical analysis,the optimal decisions of pharmaceutical enterprises and drug purchasers are obtained respectively.

Optimal Operation of Micro-energy Grids Considering Shared Energy Storage Systems and Balanced Profit Allocations

Following the unprecedented generation of renewable energy,Energy Storage Systems(ESSs)have become essential for facilitating renewable consumption and maintaining reliability in energy networks.However,providing an individual ESS to a single customer is still a luxury.Thus,this paper aims to investigate whether the Shared-ESS can assist energy savings for multiple users through Peer-to-Peer(P2P)trading.Moreover,with the increasing number of market participants in the integrated energy system(IES),a benefit allocation scheme is necessary,ensuring reasonable benefits for every user in the network.Using the multiplayer cooperative game model,the nucleolus and the Shapley value methods are adopted to evaluate the benefit allocation between multiple users.Numerical analyses based on multiple micro-energy grids are performed,so as to assess the performance of the Shared-ESS and the proposed benefit allocation scheme.The results show that the micro-energy grid cluster can save as much as 38.15%of the total energy cost with Shared-ESS being equipped.The following conclusions can be drawn:the Shared-ESS can significantly reduce the operating costs of the micro-energy grid operator,promote the consumption of renewable energy,and play the role of peak-shaving and valley-filling during different energy usage periods.In addition,it is reflected that the multiplayer cooperative game model is effective in revealing the interaction between the micro-energy grids,which makes the distribution results more reasonable.

Manufacturers’strategy for introducing remanufactured products under a government subsidy:Introduce or not?

With strong government advocacy and encouragement,many manufacturers hope to enter the remanufacturing market.Manufacturers who have entered the remanufacturing market hope to increase their profits through effective decision-making.Using game-theoretic models,this study investigates manufacturers’conditions for introducing remanufactured products and the production decisions after the introduction by constructing a consumer utility model.Our study demonstrates that manufacturers’decision-making method directly affects their decision to introduce remanufactured products.If a manufacturer plans to introduce remanufactured products,they should adopt a centralized decision-making method for the two products.Under this decision-making method,when the ratio of the government subsidy to the cost of new products is not too large or too small,the manufacturer can introduce remanufactured products.Additionally,the range of the ratio of the government subsidy to the cost of new products is related to the difference between the ratio of the cost of remanufactured products to that of new products and the substitutability of the remanufactured products.Therefore,when formulating a subsidy,the government should control it within a reasonable range and formulate differentiated subsidy strategies based on different enterprises’specific conditions to give full play to the benefits of the government subsidy.Moreover,after the manufacturer has introduced remanufactured products,the consumer surplus and manufacturer’s profit increase with the government subsidy.However,social welfare increases only when the government subsidy is within a reasonable range.Furthermore,compared with subsidizing consumers,it is found that subsidizing the manufacturer does not affect their profit,the consumer surplus,and social welfare;however,the range within which the manufacturer can introduce remanufactured products narrows.