A trusted method for multi-party decision-making based on evolutionary games in industrial Internet environments

Abstract

A credible method for multi-party decision-making based on evolutionary game in an industrial Internet environment. It includes building a decision model to obtain the utility value of decision participants; calculating the parameter ρ according to the utility value before and after the strategy change, and determining whether to change the strategy according to the parameter ρ; judging in turn whether the overall strategy selection of the decision participants reaches an equilibrium state and an evolutionarily stable proportional state according to the strategies of all decision participants, and if the evolutionarily stable proportional state is reached, it indicates that credible multi-party decision-making in the industrial Internet environment has been achieved. The present invention designs a reputation mechanism based on game theory, which will seriously affect the utility value of decision participants. When a decision participant chooses a selfish strategy, he will be severely punished and his interests will suffer serious losses, so that he dare not be dishonest and will consciously choose a cooperative strategy to honestly submit decision data, thereby enabling the multi-party decision participants within the industrial Internet to trust each other and ensure the credibility of multi-party decision-making in the industrial Internet environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial Internet, and in particular to a trusted method for multi-party decision-making based on evolutionary game in an industrial Internet environment. Background Art

[0002] As an important cornerstone of the Fourth Industrial Revolution, the Industrial Internet has been booming in many industries, which can realize efficient communication and industrial intelligence among multiple parties. With the development of the Industrial Internet, problems have been exposed in product traceability and multi-party trust. Blockchain records data such as transactions and communications within the network in a tamper-proof and completely orderly manner. It has the characteristics of decentralization, tamper-proofness and traceability. Therefore, in recent years, it has been rapidly developed and well applied in the field of Industrial Internet, thus providing a prerequisite guarantee for traceability within the Industrial Internet. However, there are still certain problems in the mutual trust of participants within the Industrial Internet.

[0003] In the industrial Internet environment, there are scenarios where multiple parties make decisions, and in this scenario, participants need to trust each other and provide their own data honestly. But in fact, some selfish participants do not provide their own data, but obtain the data of other participants at the same time, which will gain greater benefits. This requires a mechanism to reduce the benefits of selfish participants or punish them. In a decentralized environment, there is no trusted third party or an authoritative organization that has the power to impose certain penalties on selfish participants. At this time, a method is needed to punish selfish participants so that they dare not do evil. Therefore, how to enable participants to trust each other and share decision-making data is a challenge. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a trusted method for multi-party decision-making based on evolutionary game in an industrial Internet environment.

[0005] In order to achieve the above object, the multi-party decision-making trust method based on evolutionary game in the industrial Internet environment provided by the present invention includes the following steps performed in sequence:

[0006] 1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment, design a reputation mechanism based on this scenario, and build a decision-making model under this mechanism in the industrial Internet environment to obtain the utility value of decision-making participants;

[0007] 2) For decision-makers with bounded rationality, the parameter ρ is calculated based on the utility values ​​before and after the strategy change, and the decision on whether to change the strategy is made based on the parameter ρ;

[0008] 3) Each decision-maker repeats step 2), and then judges in turn based on the strategies of all decision-makers whether the overall strategy selection of the decision-makers has reached an equilibrium state and an evolutionary stable state. If an evolutionary stable state is reached, it indicates that trusted multi-party decision-making has been achieved in the industrial Internet environment.

[0009] In step 1), the specific steps of establishing a trusted scenario of multi-party decision-making in an industrial Internet environment, designing a reputation mechanism based on the scenario, and constructing a decision-making model under the mechanism in the industrial Internet environment to obtain the utility value of the decision-making participants are as follows:

[0010] 1.1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment;

[0011] Assume that the decision-making participants in the Industrial Internet have the following two strategies S = {s1, s2}:

[0012] Cooperation strategy s1: normal decision-making strategy, honestly providing one's own decision data;

[0013] Selfish strategy s2: an abnormal decision-making strategy that does not provide its own decision data and unilaterally obtains the decision data of the other party;

[0014] 1.2) Establish a decision-making information benefit model based on the above scenario;

[0015] Assume that the total number of decision-making participants in the Industrial Internet is N, and select strategy s i The number of decision-makers is Then choose strategy s among the total i The percentage of decision-makers is:

[0016]

[0017] It is composed of the proportion of each decision-making participant, indicating the proportion of the overall strategy selection of the decision-making participants;

[0018] For decision participants who all adopt the cooperation strategy s1, decision participant a who conducts decision collaboration will obtain the amount of information F(b) carried by the decision data given by the other decision participant b, while decision participant a will have his privacy information exposed due to the decision data he provided, thus causing certain losses p(a); similarly, the situation of decision participant b at this time is the same as that of decision participant a.

[0019] If decision participant a chooses the selfish strategy s2, and the other decision participant b chooses the cooperative strategy s1, then decision participant a will obtain the information F(b) of decision participant b without exposing his own privacy information.

[0020] From the above description, we can see that the selection strategy s i The decision information benefit of decision participant a is:

[0021]

[0022] in,

[0023] 1.3) Establish a decision-making cost model based on credibility;

[0024] Select strategies i The decision cost of the decision-making participants is:

[0025]

[0026] Where C represents the communication cost; Tm represents the transaction fee; Representation and credibility Inversely proportional nonlinear function;

[0027] 1.4) Based on the above decision information benefit model and decision cost model, a decision utility function is constructed to obtain the utility value of the decision participants;

[0028] The weights of decision information benefit and decision cost ω={ω1,ω2} are set as:

[0029]

[0030] Then select strategy s i The decision utility function of the decision-making participants is:

[0031]

[0032] Finally, the above decision utility function is used to obtain the selection strategy s i The utility value of the decision-making participants

[0033] In step 2), for the decision-making participants with bounded rationality, the specific steps of calculating the parameter ρ according to the utility values ​​before and after the strategy change and determining whether to change the strategy according to the parameter ρ are as follows:

[0034] 2.1) Calculate the parameter ρ based on the utility value before and after the strategy change. The formula is as follows:

[0035]

[0036] Among them, s i represents the strategy originally chosen by the decision-making participant, s j represents the strategy that the decision-maker wants to change, and s i ,sj ∈S;

[0037] 2.2) If the above calculated parameter ρ>0, it means that the decision participant a changes to strategy s j will obtain a larger utility value, then decision participant a will change the original strategy s i , and adopt strategy s j ;

[0038] 2.3) If the parameter ρ = 0, it means that the decision-maker changes to strategy s j It will not bring any additional benefits, nor will it bring any losses. For the decision-makers with limited rationality, they will randomly choose strategies.

[0039] 2.4) If the parameter ρ < 0, it means that the decision-maker changes to strategy s j Not only will it not bring any additional benefits, but it will also bring certain losses and reduce the utility value, so the decision-makers will refuse to change to strategy s j , that is, the original strategy s will still be maintained i .

[0040] In step 3), the specific steps of judging whether the overall strategy selection of the decision-making participants has reached an equilibrium state and an evolutionarily stable proportional state according to the strategies of all decision-making participants in turn, and if an evolutionarily stable proportional state is reached, indicating that a reliable multi-party decision-making in the industrial Internet environment has been achieved, are as follows:

[0041] 3.1) First, according to the selection strategy s i The proportion and utility value of decision-making participants are used to calculate the selection strategy s i The number of decision-makers is changed to determine whether the overall strategy selection of decision-makers has reached equilibrium;

[0042] Select strategies i The expression for the change in the number of decision-making participants is:

[0043]

[0044] Where t represents the unit time, which is equivalent to the number of decision-making collaborations; when the strategy s is selected i Changes in the number of decision-makers When , it means that any decision-making participant will not improve his own utility value if he unilaterally changes his strategy, that is, the decision-making participant has no motivation to change. At this time, the overall strategy selection of the decision-making participants will reach an equilibrium state;

[0045] 3.2) When the equilibrium state has been reached, it is determined whether the overall strategic choices of the decision-making participants have reached an evolutionarily stable proportional state. If so, it indicates that credible multi-party decision-making has been achieved in the industrial Internet environment;

[0046] Decision-makers are actually of limited rationality, and some decision-makers may have sudden changes in their strategies. Therefore, we need to determine whether the following formula is true:

[0047]

[0048] Among them, X′ represents the proportion of another strategy selection, ε∈(0,1) represents the proportion of strategy selection of some decision participants from X * becomes X′; when the above formula is established, it means that the mutation of the proportion state of the strategy selection of some decision-makers will not completely change the proportion state of the overall strategy selection of the decision-makers, and these decision-makers will change the proportion state of their mutation strategy selection, so that the proportion state of the overall strategy selection of the decision-makers will return to the evolutionarily stable proportion state; when or , all decision-making participants will choose cooperation strategy s1, thus realizing reliable multi-party decision-making in the Industrial Internet.

[0049] The multi-party decision-making trust method based on evolutionary game in the industrial Internet environment provided by the present invention has the following beneficial effects: the present invention designs a reputation mechanism based on game theory, which will seriously affect the utility value of decision-making participants. When decision-making participants choose selfish strategies, they will be severely punished and their interests will suffer serious losses, so that they dare not be dishonest and will consciously choose cooperative strategies to honestly submit decision data, thereby enabling multi-party decision-making participants within the industrial Internet to trust each other and ensure the credibility of multi-party decision-making in the industrial Internet environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flow chart of a trusted method for multi-party decision-making based on evolutionary game in an industrial Internet environment provided by the present invention.

[0051] Figure 2 A flow chart is established for the decision model in the present invention.

[0052] Figure 3 This is a flow chart of strategy selection for bounded rational decision-makers in the present invention. DETAILED DESCRIPTION

[0053] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] like Figure 1As shown, the multi-party decision-making trust method based on evolutionary game in the industrial Internet environment provided by the present invention includes the following steps performed in sequence:

[0055] 1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment, design a reputation mechanism based on this scenario, and build a decision-making model under this mechanism in the industrial Internet environment to obtain the utility value of decision-making participants;

[0056] like Figure 2 As shown, the specific steps are as follows:

[0057] 1.1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment;

[0058] As the infrastructure of the Industrial Internet, blockchain provides the basis for scenarios such as traceability in the Industrial Internet. Blockchain has the characteristics of being tamper-proof and traceable, so it can be used to record dishonest behaviors. Under the reputation mechanism based on blockchain, if multiple decision-making participants do evil, there will be serious consequences of dishonesty, which will have a greater impact on their utility value. Multi-party decision-making in the Industrial Internet is composed of multiple bilateral decision-making collaborations.

[0059] Assume that the decision-making participants in the Industrial Internet have the following two strategies S = {s1, s2}:

[0060] Cooperation strategy s1: normal decision-making strategy, honestly providing one's own decision data;

[0061] Selfish strategy s2: An abnormal decision-making strategy that does not provide its own decision data and unilaterally obtains the decision data of the other party.

[0062] 1.2) Establish a decision-making information benefit model based on the above scenario;

[0063] Assume that the total number of decision-making participants in the Industrial Internet is N, and select strategy s i The number of decision-makers is Then choose strategy s among the total i The percentage of decision-makers is:

[0064]

[0065] It is composed of the proportion of each decision-making participant, indicating the proportion of the overall strategy selection of the decision-making participants;

[0066] For decision participants who all adopt the cooperation strategy s1, decision participant a who conducts decision collaboration will obtain the amount of information F(b) carried by the decision data given by the other decision participant b, while decision participant a will have his privacy information exposed due to the decision data he provided, resulting in certain losses p(a); similarly, the situation of decision participant b is the same as that of decision participant a at this time.

[0067] If decision participant a chooses the selfish strategy s2, and the other decision participant b chooses the cooperative strategy s1, then decision participant a will obtain the information F(b) of decision participant b without exposing his own privacy information.

[0068] From the above description, we can see that the selection strategy s i The decision information benefit of decision participant a is:

[0069]

[0070] in,

[0071] 1.3) Establish a decision-making cost model based on credibility;

[0072] In the blockchain-based industrial Internet environment, on the one hand, transaction fees Tm will be generated; on the other hand, certain communication costs C will be incurred when making decisions, and these costs are the costs that decision-makers have to pay for participating in decision-making.

[0073] The decision-making cost model provided by the present invention is to praise and punish decision-makers based on their reputation h, that is, the level of reputation h will seriously affect the transaction fee Tm. If a decision-maker chooses the cooperative strategy s1, he only needs to pay a lower transaction fee Tm. If a decision-maker chooses the selfish strategy s2, he needs to pay a high transaction fee Tm, which increases the cost of dishonesty. Based on this, the decision-maker who chooses the strategy s i The decision cost of the decision-making participants is:

[0074]

[0075] Where C represents the communication cost; Tm represents the transaction fee; Representation and credibility A nonlinear function that is inversely proportional to decreases, ∝ will increase sharply; on the contrary, as the credibility As increases, ∝ will decrease sharply.

[0076] 1.4) Based on the above decision information benefit model and decision cost model, a decision utility function is constructed to obtain the utility value of the decision participants;

[0077] Both decision information benefits and decision costs can be understood as a kind of benefit of decision participants, which has a direct impact on the utility value. Therefore, the weights of decision information benefits and decision costs ω = {ω1, ω2} are set as:

[0078]

[0079] Then select strategy s i The decision utility function of the decision-making participants is:

[0080]

[0081] Finally, the above decision utility function is used to obtain the selection strategy s i The utility value of the decision-making participants

[0082] 2) For decision-makers with bounded rationality, the parameter ρ is calculated based on the utility values ​​before and after the strategy change, and the decision on whether to change the strategy is made based on the parameter ρ;

[0083] like Figure 3 As shown, the specific steps are as follows:

[0084] 2.1) Calculate the parameter ρ based on the utility value before and after the strategy change. The formula is as follows:

[0085]

[0086] Among them, s i represents the strategy originally chosen by the decision-making participant, s j represents the strategy that the decision-maker wants to change, and s i ,s j ∈S;

[0087] 2.2) If the above calculated parameter ρ>0, it means that the decision participant a changes to strategy s j will obtain a larger utility value, then decision participant a will change the original strategy s i , and adopt strategy s j ;

[0088] 2.3) If the parameter ρ = 0, it means that the decision-maker changes to strategy s j It will not bring any additional benefits, nor will it bring any losses. For the decision-makers with limited rationality, they will randomly choose strategies.

[0089] 2.4) If the parameter ρ < 0, it means that the decision-maker changes to strategy s j Not only will it not bring any additional benefits, but it will also bring certain losses and reduce the utility value, so the decision-makers will refuse to change to strategy s j, that is, the original strategy s will still be maintained i .

[0090] 3) Each decision-maker repeats step 2), and then judges in turn based on the strategies of all decision-makers whether the overall strategy selection of the decision-makers has reached an equilibrium state and an evolutionarily stable proportional state. If an evolutionarily stable proportional state is reached, it indicates that trusted multi-party decision-making has been achieved in the industrial Internet environment.

[0091] The specific steps are as follows:

[0092] 3.1) First, according to the above selection strategy s i The proportion and utility value of decision-making participants are used to calculate the selection strategy s i The number of decision-makers is changed to determine whether the overall strategy selection of decision-makers has reached equilibrium;

[0093] Select strategies i The expression for the change in the number of decision-making participants is:

[0094]

[0095] Where t represents the unit time, which is equivalent to the number of decision-making collaborations; when the strategy s is selected i Changes in the number of decision-makers When , it means that any decision-making participant will not improve his own utility value if he unilaterally changes his strategy, that is, the decision-making participant has no motivation to change. At this time, the overall strategy selection of the decision-making participants will reach an equilibrium state;

[0096] 3.2) When the equilibrium state has been reached, it is determined whether the overall strategic choices of the decision-making participants have reached an evolutionarily stable proportional state. If so, it indicates that credible multi-party decision-making has been achieved in the industrial Internet environment;

[0097] Decision-makers are actually of limited rationality, and some decision-makers may have sudden changes in their strategies. Therefore, we need to determine whether the following formula is true:

[0098]

[0099] Among them, X′ represents the proportion of another strategy selection, ε∈(0,1) represents the proportion of strategy selection of some decision participants from X * becomes X′. When the above formula is established, the mutation of the proportion state of the strategy selection of some decision-makers will not completely change the proportion state of the overall strategy selection of the decision-makers, and these decision-makers will change the proportion state of their mutated strategy selection, so that the proportion state of the overall strategy selection of the decision-makers will return to the evolutionarily stable proportion state; when or , all decision-making participants will choose cooperation strategy s1, thus realizing reliable multi-party decision-making in the Industrial Internet.

Claims

1. A trusted multi-party decision-making method based on evolutionary game in an industrial Internet environment, characterized in that: the trusted multi-party decision-making method comprises the following steps performed in sequence: 1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment, design a reputation mechanism based on this scenario, and build a decision-making model under this mechanism in the industrial Internet environment to obtain the utility value of decision-making participants; 2) For decision-makers with bounded rationality, the parameter ρ is calculated based on the utility values ​​before and after the strategy change, and the decision on whether to change the strategy is made based on the parameter ρ; 3) Each decision-maker repeats step 2), and then judges whether the overall strategy selection of the decision-makers has reached an equilibrium state and an evolutionarily stable proportional state based on the strategies of all decision-makers. If an evolutionarily stable proportional state is reached, it indicates that a credible multi-party decision has been achieved in the industrial Internet environment; In step 1), the specific steps of establishing a trusted scenario of multi-party decision-making in an industrial Internet environment, designing a reputation mechanism based on the scenario, and constructing a decision-making model under the mechanism in the industrial Internet environment to obtain the utility value of the decision-making participants are as follows: 1.1) Establish a trusted scenario for multi-party decision-making in the industrial Internet environment; Assume that the decision-making participants in the Industrial Internet have the following two strategies S = {s1, s2}: Cooperation strategy s1: normal decision-making strategy, honestly providing one's own decision data; Selfish strategy s2: an abnormal decision-making strategy that does not provide its own decision data and unilaterally obtains the decision data of the other party; 1.2) Establish a decision-making information benefit model based on the above scenario; Assume that the total number of decision-making participants in the Industrial Internet is N, and select strategy s i The number of decision-makers is Then choose strategy s among the total i The percentage of decision-makers is: It is composed of the proportion of each decision-making participant, indicating the proportion of the overall strategy selection of the decision-making participants; For the decision participants who all adopt the cooperation strategy s1, the decision participant a who conducts decision collaboration will obtain the information F(b) carried by the decision data given by the other decision participant b, while the decision participant a will have his privacy information exposed due to the decision data he provided, thus causing a certain loss p(a); similarly, the situation of decision participant b is the same as that of decision participant a. If decision participant a chooses the selfish strategy s2, and the other decision participant b chooses the cooperative strategy s1, then decision participant a will obtain the information F(b) of decision participant b without exposing his own private information; From the above description, we can see that the selection strategy s i The decision information benefit of decision participant a is: in, 1.3) Establish a decision-making cost model based on credibility; Select strategies i The decision cost of the decision-making participants is: in, C represents the communication cost; Tm represents the transaction fee; Representation and credibility Inversely proportional nonlinear function; 1.4) Based on the above decision information benefit model and decision cost model, a decision utility function is constructed to obtain the utility value of the decision participants; The weights of decision information benefit and decision cost ω={ω1,ω2} are set as: Then select strategy s i The decision utility function of the decision-making participants is: Finally, the above decision utility function is used to obtain the selection strategy s i The utility value of the decision-making participants 2. The trusted multi-party decision-making method based on evolutionary game in the industrial Internet environment according to claim 1 is characterized by: In step 2), for the decision-making participants with bounded rationality, the specific steps of calculating the parameter ρ according to the utility values ​​before and after the strategy change and determining whether to change the strategy according to the parameter ρ are as follows: 2.1) Calculate the parameter ρ based on the utility value before and after the strategy change. The formula is as follows: Among them, s i represents the strategy originally chosen by the decision-making participant, s j represents the strategy that the decision-maker wants to change, and s i ,s j ∈S; 2.2) If the above calculated parameter ρ>0, it means that the decision participant a changes to strategy s j will obtain a larger utility value, then decision participant a will change the original strategy s i , and adopt strategy s j ; 2.3) If the parameter ρ = 0, it means that the decision-maker changes to strategy s j It will not bring any additional benefits, nor will it bring any losses. For the decision-makers with limited rationality, they will randomly choose strategies. 2.4) If the parameter ρ < 0, it means that the decision-maker changes to strategy s j Not only will it not bring any additional benefits, but it will also bring certain losses and reduce the utility value, so the decision-makers will refuse to change to strategy s j , that is, the original strategy s will still be maintained i .

3. The trusted multi-party decision-making method based on evolutionary game in the industrial Internet environment according to claim 1 is characterized by: In step 3), the specific steps of judging whether the overall strategy selection of the decision-making participants has reached an equilibrium state and an evolutionarily stable proportional state according to the strategies of all decision-making participants in turn, and if an evolutionarily stable proportional state is reached, indicating that a reliable multi-party decision-making in the industrial Internet environment has been achieved, are as follows: 3.1) First, according to the selection strategy s i The proportion and utility value of decision-making participants are used to calculate the selection strategy s i The number of decision-makers is changed to determine whether the overall strategy selection of decision-makers has reached equilibrium; Select strategies i The expression for the change in the number of decision-making participants is: Where t represents the unit time, which is equivalent to the number of decision-making collaborations; when the strategy s is selected i Changes in the number of decision-makers When , it means that any decision-making participant will not improve his own utility value if he unilaterally changes his strategy, that is, the decision-making participant has no motivation to change. At this time, the overall strategy selection of the decision-making participants will reach an equilibrium state; 3.2) When the equilibrium state has been reached, it is determined whether the overall strategic choices of the decision-making participants have reached an evolutionarily stable proportional state. If so, it indicates that credible multi-party decision-making has been achieved in the industrial Internet environment; Decision-makers are actually of limited rationality, and some decision-makers may have sudden changes in their strategies. Therefore, we need to determine whether the following formula is true: Among them, X′ represents the proportion of another strategy selection, ε∈(0,1) represents the proportion of strategy selection of some decision participants from X * becomes X′; when the above formula is established, it means that the mutation of the proportion state of the strategy selection of some decision-makers will not completely change the proportion state of the overall strategy selection of the decision-makers, and these decision-makers will change the proportion state of their mutation strategy selection, so that the proportion state of the overall strategy selection of the decision-makers will return to the evolutionarily stable proportion state; when or , all decision-making participants will choose cooperation strategy s1, thus realizing reliable multi-party decision-making in the Industrial Internet.

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