Consensus-based pareto alliance conflict analysis method, apparatus, device, and medium

Abstract

This application relates to a consensus-based Pareto alliance conflict analysis method, apparatus, equipment, and medium, belonging to the field of emergency rescue decision-making technology. The method includes: constructing a conflict graph model of emergency rescue conflicts; constructing a consensus-based Pareto alliance improvement matrix for focal alliances based on the alliance division results and the conflict graph model; under the condition that the focal alliances do not know the alliances of their opponents, constructing the alliance domain composed of the entire alliance of opponents and the entire alliance set, and constructing a corresponding consensus-based hybrid Pareto alliance improvement matrix, while dividing the alliances into trusted and untrusted opponent alliances; constructing consensus-based Pareto alliance stability judgment rules under hybrid countermeasures, and performing stability analysis to obtain the equilibrium result of emergency rescue conflicts, assisting decision-makers in executing emergency rescue decisions. This method can effectively improve the rationality, feasibility, and practicality of emergency rescue conflict coordination schemes.

Description

Technical Field

[0001] This application relates to the field of emergency rescue decision-making technology, and in particular to a consensus-based Pareto alliance conflict analysis method, apparatus, equipment and medium. Background Technology

[0002] In emergency rescue decision-making scenarios, the conflict process involves multiple independent decision-makers. Each decision-maker engages in strategic games and checks and balances based on their own objectives in emergency rescue. The interaction of their decision choices collectively determines the evolution of the entire emergency rescue decision-making conflict scenario. The essence of emergency rescue decision-making conflict is a divergence of interests, rooted in the intensification of contradictions caused by different stakeholders vying for limited rescue resources and seeking maximum resource advantage during the emergency rescue process. Furthermore, influenced by the complexity of the emergency rescue conflict process itself and the uncertainty of the decision-making behavior of each decision-maker, the conflicting parties may also form complex alliances and counterbalancing behaviors through repeated games and strategic interactions.

[0003] To address this conflict in emergency response decision-making scenarios, existing research methods typically employ the concepts of coalition improvement or Pareto coalition improvement. These methods regulate and analyze alliance and counter-alliance behaviors in emergency response scenarios by assessing whether coalitions will deviate from their current state and whether the target state has reached equilibrium. However, these methods generally rely on idealized assumptions. On the one hand, they assume all coalitions maintain consistent criteria for state improvement; on the other hand, they assume that each coalition's countermeasures against its adversary in emergency response decision-making are homogeneous. However, in real-world emergency response decision-making conflicts, different coalition members exhibit significant differences in their focus on emergency response objectives, information awareness, and risk preferences. This leads to varying degrees of acceptance of the same state among different coalitions. If a single, homogeneous set of coalition improvement and counter-alliance rules is still used, it will be difficult to accurately depict the dynamic evolution of alliance behavior in real-world emergency response decision-making conflicts, thus affecting the accuracy and reliability of the stability analysis results. Summary of the Invention

[0004] Therefore, it is necessary to provide a consensus-based Pareto alliance conflict analysis method, apparatus, equipment, and medium to address the aforementioned technical problems.

[0005] A consensus-based Pareto alliance conflict analysis method, the method comprising:

[0006] To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

[0007] In one embodiment, the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict are obtained, and a conflict graph model is constructed, represented as follows: ;in, For decision-makers For the number of decision-makers and This includes both individual decision-makers and organizational decision-makers; This is the set of feasible states, indicating all feasible states formed by different combinations of rescue strategies adopted by the decision-maker. Indicates the first One state; For the set of state transition arcs, For decision-makers The set of all one-step unilateral moves. This represents the set of preference relationships corresponding to each decision-maker. Indicates decision-makers Binary preference information regarding state reflects the interests and objectives of decision-makers in emergency response conflicts, among which... Indicates decision-makers Preferring one of two states. Indicates decision-makers The preference for two states is the same.

[0008] In one embodiment, the method further includes: Decision-makers are constructed based on conflict diagram models. The preference matrix and state transition matrix are expressed as follows: , , , as well as ;in, , and They represent the decision-makers. The preference improvement matrix, preference equivalence matrix, and preference inferiority matrix. and They represent the decision-makers. unilateral shift matrix and unilateral improvement matrix; Indicates decision-makers exist and Preference between two states ; Indicates decision-makers right and The two states have the same degree of preference; Indicates decision-makers exist and Preference between two states .

[0009] In one embodiment, the decision-maker set is partitioned based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance partitioning results and the conflict graph model, including: The set of decision-makers is partitioned based on alliance relationships, resulting in a set containing at least two alliances. And for the first Alliance When conducting the analysis, It is called the Focus League, while its opponents belong to the same league. The term "opponent alliance" refers to the total number of members in an opponent alliance. ;in, For decision-makers For set The total number of alliances in the country; Targeting the Focus Alliance and any state comparison pair ,according to Internal state Relative to state Number of decision-makers who share the same preference judgment and Total number of members The ratio, calculate Compare states Consent support for preference relationships , is represented as: ; in, Indicates about state Superior state Preference judgment, Indicates about state Equivalent to state Preference judgment, Indicates about state Inferior state Preference judgment; Based on approval ratings and Corresponding consensus threshold ,calculate The consensus-based Pareto improvement preference matrix is ​​expressed as: ; in, Used to measure preference state Superior state Does the member ratio meet the requirements? The consensus requires, Used to measure whether it is a focus alliance any decision-maker in Everyone believes Superior to or equivalent to ,symbol This represents the Hadamard product operator. Indicates decision-makers think Superior to or equivalent to The consensus threshold is determined based on the alliance's internal consultation mechanism, alliance organizational rules, historical rescue decision-making patterns, or external input parameters. Further according to Consensus-based Pareto Improved Preference Matrix , build The consensus-based Pareto alliance improvement matrix is ​​expressed as: ; in, express Consensus-based Pareto alliance improvement set express Control in state Joint unilateral movement at the location, The methods of obtaining it include: For all Both are true; if and ,but ,and ;like , , ,but and The premise is ;in, Represents the union, express The set of all decision-makers who make the last move during the process of legal unilateral movement from one state to another is used. The set of feasible states Indicates decision-makers In state s A set of unilateral moves at a given location.

[0010] In one embodiment, the entire alliance and the alliance domain are divided into trusted adversary alliances and untrusted adversary alliances by considering differentiated responses to different rescue strategy shifts in the focus alliance, including: Based on pre-defined behavioral constraints or historical game behavior data, we identify whether each adversary alliance considers its overall interests when implementing countermeasures. If an adversary alliance needs to satisfy a consensus-based Pareto superiority relationship between the countermeasure target state and the original state for the alliance as a whole when implementing countermeasures, then it is classified as a trustworthy adversary alliance. and define a trusted adversary alliance The consensus-based Pareto alliance improvement matrix adopted for countermeasures is as follows: Otherwise, classify it as an alliance of untrusted adversaries. and define untrusted adversary alliances The alliance movement matrix adopted for countermeasures is ;in, and These are the sets consisting of all trusted adversary alliances and all untrusted adversary alliances under the current analysis.

[0011] In one embodiment, constructing a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain includes: All League Focus Alliance Focus Alliance The set of all alliance scenarios consisting of all opponents is called the alliance domain. ;in, For decision-makers; Building the entire alliance Consensus-based Hybrid Pareto Alliance Improvement Matrix , is represented as: ; Among them, for , ;for ,exist ,and , , Indicates from state Move to state The number of effective moves made across the entire alliance. Let be the total number of effective moves in the entire alliance; and for any three matrix A new operation is defined as ,That Item element is represented as ; For the entire alliance, its representation includes non-empty alliances. The set of all decision-makers in the alliance is the alliance situation for any type of opponent, and for any sub-alliance number in the entire alliance. , ,have ; The set of feasible states For any state comparison pair, Represents a matrix The sign function, Not included in the entire league The set of all other opposing alliances, symbol The difference operator for sets; Constructing the domain of alliances The consensus-based hybrid Pareto alliance improvement matrix is ​​represented as follows: : ; in, For the alliance domain, it represents the composition of the adversaries. A collection composed of all alliances For the first A full alliance.

[0012] In one embodiment, the consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior includes: Focus Alliance and ,state yes The consensus-based Pareto alliance Nash stability is achieved if and only if , recorded as ;in, It is a set of elements where all elements equal 1. dimensional vector, for A consensus-based Pareto alliance improvement matrix Indicates the first The item is 1 and the rest are 0. dimensional vector, express transpose, It is the set of all states that satisfy consensus-based Pareto-aligned Nash stability during a conflict; make and and given a 3D matrix ,state yes Consensus-based hybrid Pareto alliances (GMRs) are stable if and only if , recorded as , for Consensus-based Pareto non-improvement preference matrix This indicates that each item is 1. matrix, for The consensus-based Pareto improvement preference matrix, where the superscript T denotes matrix transpose. It is the set of all states that satisfy consensus-based Pareto-aligned GMR stability during a conflict; make and and given a 3D matrix ,in ,state It is an alliance Consensus-based hybrid Pareto alliance SMR is stable if and only if , recorded as ; for The matrix form of the joint unilateral movement, symbol This represents the Hadamard product operator. It is the set of all states that satisfy consensus-based Pareto-aligned SMR stability during a conflict; A strong equilibrium state is defined as a state that simultaneously satisfies consensus-based hybrid Pareto alliance Nash stability, consensus-based hybrid Pareto alliance GMR stability, and consensus-based hybrid Pareto alliance SMR stability.

[0013] A consensus-based Pareto alliance conflict analysis apparatus, the apparatus comprising: The first module is used to obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in emergency rescue conflicts, and to construct a conflict graph model. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing its own rescue strategy. The second module is used to divide the decision-maker set based on alliance relationships, and construct a consensus-based Pareto alliance improvement matrix for focus alliances based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. The third module is used to enumerate all feasible alliance schemes that satisfy the condition that a single opponent belongs to only one sub-alliance and that the opponent is fully involved, under the condition that the focus alliance has unknown opponents. It constructs the alliance domain composed of the entire alliance of opponents and the entire alliance set, and constructs a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into trusted opponent alliances and untrusted opponent alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. The fourth module is used to construct consensus-based Pareto alliance stability judgment rules under hybrid countermeasure behavior based on the consensus-based Pareto alliance improvement matrix of the focus alliance, the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, and to conduct stability analysis to obtain the equilibrium results of emergency rescue conflicts. Finally, based on the equilibrium results, the module analyzes the causes and evolution of emergency rescue conflicts, thereby assisting decision-makers in making emergency rescue decisions.

[0014] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps: To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

[0015] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor: To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

[0016] The aforementioned consensus-based Pareto alliance conflict analysis method, apparatus, equipment, and medium have the following beneficial effects: First, by constructing a conflict graph model, a structured and visual representation of game relationships and state evolution in emergency rescue conflict scenarios is achieved, laying a clear logical foundation for subsequent alliance decision analysis; simultaneously, based on the alliance relationship, the decision-maker set is divided, and the consensus-based Pareto alliance improvement matrix of the focus alliance is constructed by combining the alliance division results with the conflict graph model. This fully considers the alliance collaboration characteristics and consensus decision-making needs of multiple stakeholders in emergency rescue, and accurately quantifies the feasible Pareto alliance improvement space of the focus alliance, effectively improving the feasibility and pertinence of emergency rescue conflict coordination schemes; secondly, by addressing the unknown aspects of the focus alliance... Under the condition of adversary alliances, a universe of alliances is constructed, consisting of a full alliance of adversaries and a set of full alliances. Within the full alliance and the universe of alliances, credible adversary alliances and untrustworthy adversary alliances are divided. Then, a corresponding consensus-based hybrid Pareto alliance improvement matrix is ​​generated as a counter-movement rule for adversary alliances, which fully covers various alliance possibilities and behavioral characteristics of adversaries. Furthermore, after constructing consensus-based Pareto alliance stability determination rules under hybrid counter-movement behavior, equilibrium results are obtained through stability analysis. This can accurately analyze the causes and evolution of emergency rescue conflicts, providing scientific and comprehensive decision support for decision-makers, effectively improving the rationality, feasibility, and operability of emergency rescue conflict coordination plans, and ensuring the scientific and collaborative nature of emergency rescue decisions. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a consensus-based Pareto alliance conflict analysis method in one embodiment. Figure 2 This is a schematic diagram illustrating an implementation of a consensus-based Pareto alliance conflict analysis method in one embodiment. Figure 3 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] In one embodiment, such as Figure 1 and Figure 2 As shown, a consensus-based Pareto alliance conflict analysis method is provided, including the following steps: Step 1: Obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in the emergency rescue conflict, and construct a conflict graph model; where a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing its own rescue strategy.

[0020] The specific process of constructing a conflict graph model is as follows: Obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships corresponding to each decision-maker in the emergency rescue conflict; then construct the conflict graph model, represented as follows: ;in, For decision-makers For the number of decision-makers and This includes both individual decision-makers and organizational decision-makers; This is the set of feasible states, indicating all feasible states formed by different combinations of rescue strategies adopted by the decision-maker. Indicates the first One state; For the set of state transition arcs, For decision-makers The set of all one-step unilateral moves. This represents the set of preference relationships corresponding to each decision-maker. Indicates decision-makers Binary preference information regarding state reflects the interests and objectives of decision-makers in emergency response conflicts, among which... Indicates decision-makers Preferring one of two states. Indicates decision-makers The preference for two states is the same.

[0021] Furthermore, after constructing the conflict graph model, decision-makers are also constructed based on the conflict graph model. The preference matrix includes: , , ;in, , and They represent the decision-makers. The preference improvement matrix, preference equivalence matrix, and preference inferiority matrix; Based on the decision-maker's state transitions and preference relationships, a decision-maker can be constructed. In state s The set of unilateral shifts and the set of unilateral improvements at a given point are represented as follows: , ; Among them, unilateral improvement indicates that the decision-maker prefers the state after unilateral movement to the initial state; Based on this, decision-makers can be constructed. The unilateral shift matrix and the unilateral improvement matrix are expressed as follows: , ; in, and They represent the decision-makers. unilateral shift matrix and unilateral improvement matrix; Indicates decision-makers exist and Preference between two states ; Indicates decision-makers right and The two states have the same degree of preference; Indicates decision-makers exist and Preference between two states .

[0022] Step 2: Divide the decision-maker set based on the alliance relationship, and construct a consensus-based Pareto alliance improvement matrix for focus alliances based on the alliance division results and the conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division.

[0023] Specifically, step 2 includes: The set of decision-makers is partitioned based on alliance relationships, resulting in a set containing at least two alliances. And for the first Alliance When conducting the analysis, It is called the Focus League, while its opponents belong to the same league. The term "opponent alliance" refers to the total number of members in an opponent alliance. Furthermore, there may exist a set of adversary alliances consisting of one or more adversary alliances; among which, For decision-makers For set The total number of alliances in the country; Targeting the Focus Alliance and any state comparison pair ,according to Internal state Relative to state Number of decision-makers who share the same preference judgment and Total number of members The ratio, calculate Compare states Consent support for preference relationships , is represented as: ; in, Indicates about state Superior state Preference judgment, Indicates about state Equivalent to state Preference judgment, Indicates about state Inferior state Preference judgment; Based on approval ratings and Corresponding consensus threshold ,calculate The consensus-based Pareto improvement preference matrix is ​​expressed as: ; in, Used to measure preference state Superior state Does the member ratio meet the requirements? The consensus requires, Used to measure whether it is a focus alliance any decision-maker in Everyone believes Superior to or equivalent to ,symbol This represents the Hadamard product operator. Indicates decision-makers think Superior to or equivalent to The consensus threshold is determined based on the alliance's internal negotiation mechanism, organizational rules, historical rescue decision-making patterns, or external input parameters. When the consensus threshold is high, only candidate states unanimously agreed upon by a majority or even all members of the alliance are considered improvements. When the consensus threshold is low, more candidate states with local benefits but no overall disadvantage are acceptable. Therefore, the alliance... The consensus-based Pareto non-improvement preference matrix can be defined as follows: , This indicates that each item is 1. matrix.

[0024] It should be understood that by introducing the degree of consent and consensus threshold, this application has achieved a refined and quantitative representation of the standards for recognizing improvement schemes within different alliances. This effectively improves the adaptability of the alliance improvement judgment rules to the differences in cognition and heterogeneity of decision-making preferences among multiple stakeholders in real emergency rescue conflict scenarios, and enhances the scientific nature and scenario fit of the scheme judgment.

[0025] Further according to Consensus-based Pareto Improved Preference Matrix , build The consensus-based Pareto alliance improvement matrix is ​​expressed as: ; in, express Consensus-based Pareto alliance improvement set express Control in state Joint unilateral movement at the location, The methods of obtaining it include: For all Both are true; if and ,but ,and ;like , , ,but and The premise is ;in, Represents the union, express In the process of transitioning from one state to another using legal unilateral moves, a set is formed of all the decision-makers who made the last move. The set of feasible states Indicates decision-makers In state s The set of unilateral moves at a given location. The matrix form of the joint unilateral movement is obtained as follows: .

[0026] Furthermore, in Based on this, if the alliance If each member in the alliance makes a unilateral move, then the alliance can be obtained. Control in state Joint unilateral improvement set at the location The method of obtaining it is as follows: For all Both are true; if and ,but ,and ;if , , ,but and The premise is ;in, This indicates the adoption of a legitimate unilateral improvement from s Transferred to The set of all decision-makers who make the final move during the process.

[0027] Step 3: Under the condition that the focus alliance has no unknown adversary alliance, enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved, construct the alliance domain composed of the full alliance of adversaries and the full alliance set, and construct the consensus-based hybrid Pareto alliance improvement matrix of the full alliance and the alliance domain; wherein, the full alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance.

[0028] The specific rules for distinguishing between trusted adversary alliances and untrusted adversary alliances are as follows: Based on pre-defined behavioral constraints or historical game behavior data, we identify whether each adversary alliance considers its overall interests when implementing countermeasures. If an adversary alliance needs to satisfy a consensus-based Pareto superiority relationship between the countermeasure target state and the original state for the alliance as a whole when implementing countermeasures, then it is classified as a trustworthy adversary alliance. and define a trusted adversary alliance The consensus-based Pareto alliance improvement matrix adopted for countermeasures is as follows: Otherwise, classify it as an alliance of untrusted adversaries. and define untrusted adversary alliances The alliance movement matrix adopted for countermeasures is ;in, and These represent the sets of all trustworthy adversary alliances and all untrustworthy adversary alliances under the current analysis. Specifically, the algorithm extracts the path selection characteristics, profit change characteristics, post-countermeasure state distribution characteristics, and countermeasure result characteristics of each adversary alliance in historical conflicts. These characteristics are then input into a classification model, clustering model, rule matching model, or threshold determination model, and the output is a trustworthiness category.

[0029] It should be understood that by distinguishing between trusted adversary alliances and untrusted adversary alliances, and constructing state transition relationships under mixed countermeasure behavior conditions within a unified framework, this application can improve the ability to characterize complex countermeasure behaviors, thereby enhancing the scientific nature of emergency rescue conflict assessment and assisting analysts in dealing with complex emergency rescue conflict issues.

[0030] In conflicts involving multiple alliance entities, information asymmetry and other factors make it difficult for any alliance entity to determine the alliance status of its opponents. To fully address the uncertainties arising from various possible scenarios, this application enumerates all feasible alliance schemes that satisfy the conditions of a single opponent belonging to only one sub-alliance and full opponent participation, constructing an alliance domain consisting of the entire alliance of opponents and the set of entire alliances. The entire alliance... Focus Alliance Focus Alliance The set of all alliance scenarios consisting of all opponents is called the alliance domain. .

[0031] Specifically, For the entire alliance, its representation includes non-empty alliances. The set of all decision-makers in the alliance is the alliance situation for any type of opponent, and for any sub-alliance number in the entire alliance. , ,have Among them, if the state It can be by Some alliances in the game move from the entire alliance. Arriving, but not able to move twice consecutively, is called... yes exist A full coalition move at a given point, consisting of the set of all similar states. The method of obtaining it is: (i) For all ,have (ii) For each ,if ,but and (iii) If , , ,but and The premise is .

[0032] in, Indicates the movement of the entire alliance through effective movement ( (In the game, alliances cannot move twice consecutively.) s Move to The set of all the last-moving alliances, and the matrix form of all alliance moves is: ; and Similarly, if the state Improvements can only be achieved by certain alliances through consensus-based Pareto alliances. Arriving, but not able to move twice consecutively, is called... yes exist A consensus-based Pareto alliance improvement set The method of obtaining it is as follows: (i) For all ,have ; (ii) For each ,if ,but and ; (iii) If , , ,but and The premise is ; in, This indicates that the entire alliance has achieved improvements through effective consensus-based Pareto alliances. s Move to The set of all the last-moving alliances, and the matrix form of the consensus-based Pareto alliance improvement for the entire alliance is: .

[0033] Building on the basis of the entire alliance For the alliance domain, it represents the composition of the adversaries. A collection composed of all alliances For the first A complete alliance. Alliance domain. In state A consensus-based Pareto alliance improvement set The method of obtaining it is: .

[0034] All League In state Consensus-based Hybrid Pareto Alliance Improvement Set The method of obtaining it is: (i) For all ,have ; (ii) If and ,but and .if and ,but and ; (iii) If , , as well as ,but and .if , , and ,but and .

[0035] Each opposing alliance can be determined from its status. State transitions are performed through joint unilateral moves or consensus-based Pareto improvements.

[0036] Alliance discourse encompassing the entire alliance of all its opponents. In state A consensus-based improved set of hybrid Pareto alliances. The method of obtaining it is: .

[0037] Building upon a consensus-based hybrid Pareto alliance improvement set, a full alliance is constructed. Consensus-based Hybrid Pareto Alliance Improvement Matrix , is represented as: ; Among them, for , ;for ,exist ,and , , Indicates from state Move to state The number of effective moves made across the entire alliance. Let be the total number of effective moves in the entire alliance; and for any three matrix A new operation is defined as ,That Item element is represented as ; Represents a matrix The sign function, As the non-empty alliance in the entire alliance, Not included in the entire league The set of all other opposing alliances, symbol The difference operator for sets.

[0038] Further construct the alliance domain The consensus-based hybrid Pareto alliance improvement matrix is ​​represented as follows: : ; in, For the alliance domain, it represents the composition of the adversaries. A collection composed of all alliances For the first A full alliance.

[0039] Step 4: Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, construct the consensus-based Pareto alliance stability judgment rule under hybrid countermeasure behavior, and conduct stability analysis to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, analyze the causes and evolution of emergency rescue conflict, thereby assisting decision-makers in executing emergency rescue decisions.

[0040] It should be understood that for any state to be determined in an emergency rescue scenario, the stability of the state can be determined based on the following conditions: whether the focus coalition still has consensus-based Pareto coalition improvements; whether the entire coalition composed of adversary coalitions can prevent the improvement through hybrid countermeasures; and whether the focus coalition can continue to implement the improvement after countermeasures. These conditions determine whether the state satisfies consensus-based hybrid Pareto coalition Nash stability (CPCNash), consensus-based hybrid Pareto coalition GMR stability (CMPCGMR), and consensus-based hybrid Pareto coalition SMR stability (CMPCSMR). The specific rules for determining consensus-based Pareto coalition stability under hybrid countermeasures are as follows: Focus Alliance and ,state yes The consensus-based Pareto alliance Nash stability is achieved if and only if , recorded as ;in, It is a set of elements where all elements equal 1. dimensional vector, for A consensus-based Pareto alliance improvement matrix Indicates the first The item is 1 and the rest are 0. dimensional vector, express transpose, It is the set of all states that satisfy consensus-based Pareto-aligned Nash stability during a conflict; make and and given a 3D matrix ,state yes Consensus-based hybrid Pareto alliances (GMRs) are stable if and only if , recorded as , for Consensus-based Pareto non-improvement preference matrix This indicates that each item is 1. matrix, for The consensus-based Pareto improvement preference matrix, where the superscript T denotes matrix transpose. It is the set of all states that satisfy consensus-based Pareto-aligned GMR stability during a conflict; make and and given a 3D matrix ,in ,state It is an alliance Consensus-based hybrid Pareto alliance SMR is stable if and only if , recorded as ; for The matrix form of the joint unilateral movement, symbol This represents the Hadamard product operator. It is the set of all states that satisfy consensus-based Pareto-aligned SMR stability during a conflict; A strong equilibrium state is defined as a state that simultaneously satisfies consensus-based hybrid Pareto alliance Nash stability, consensus-based hybrid Pareto alliance GMR stability, and consensus-based hybrid Pareto alliance SMR stability.

[0041] Based on the equilibrium results obtained from the consensus-based Pareto alliance stability determination rule analysis under the above-mentioned mixed countermeasures, the emergency rescue conflict situation corresponding to each strong equilibrium result can be analyzed one by one to identify the causes of emergency rescue conflicts and possible evolutionary results. Starting from the current situation of emergency rescue conflicts, possible emergency rescue decision evolution links can be analyzed. Based on the implementation of rescue strategies in each situation, it can be determined which strategies are definitely adopted by all parties in the conflict. Finally, the equilibrium analysis results can be used to assist all parties in emergency rescue conflicts in making decisions.

[0042] The aforementioned consensus-based Pareto alliance conflict analysis method first constructs a conflict graph model to achieve a structured and visual representation of game relationships and state evolution in emergency rescue conflict scenarios, laying a clear and rigorous logical foundation for subsequent alliance decision analysis. Simultaneously, it divides the decision-maker set based on alliance relationships and combines the alliance division results with the conflict graph model to construct a consensus-based Pareto alliance improvement matrix for focus alliances. This not only fully aligns with the multi-stakeholder alliance collaboration characteristics and consensus decision-making needs in emergency rescue but also accurately quantifies the feasible Pareto alliance improvement space for focus alliances, effectively enhancing the feasibility and relevance of emergency rescue conflict coordination solutions. Secondly, under the condition that the focus alliance has no known adversary alliances, a coalition discourse consisting of the entire coalition of adversaries and the entire coalition set is constructed. Within the entire coalition and the coalition discourse, credible adversary coalitions and untrustworthy adversary coalitions are divided. Then, a corresponding consensus-based hybrid Pareto coalition improvement matrix is ​​generated as a counter-movement rule for adversary coalitions, which comprehensively covers various adversary alliance possibilities and behavioral characteristics. On this basis, a consensus-based Pareto coalition stability determination rule under hybrid counter-movement behavior is constructed. Through stability analysis, equilibrium results are obtained, which can accurately analyze the causes and evolution of emergency rescue conflicts, provide scientific and comprehensive decision support for decision-makers, significantly improve the rationality, feasibility and operability of emergency rescue conflict coordination plans, and ensure the scientific nature and multi-stakeholder collaboration of emergency rescue decisions.

[0043] In one embodiment, a consensus-based Pareto alliance conflict analysis apparatus is provided, comprising: The first module is used to obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in emergency rescue conflicts, and to construct a conflict graph model. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing its own rescue strategy. The second module is used to divide the decision-maker set based on alliance relationships, and construct a consensus-based Pareto alliance improvement matrix for focus alliances based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. The third module is used to enumerate all feasible alliance schemes that satisfy the condition that a single opponent belongs to only one sub-alliance and that the opponent is fully involved, under the condition that the focus alliance has unknown opponents. It constructs the alliance domain composed of the entire alliance of opponents and the entire alliance set, and constructs a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into trusted opponent alliances and untrusted opponent alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. The fourth module is used to construct consensus-based Pareto alliance stability judgment rules under hybrid countermeasure behavior based on the consensus-based Pareto alliance improvement matrix of the focus alliance, the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, and to conduct stability analysis to obtain the equilibrium results of emergency rescue conflicts. Finally, based on the equilibrium results, the module analyzes the causes and evolution of emergency rescue conflicts, thereby assisting decision-makers in making emergency rescue decisions.

[0044] Specific limitations regarding the consensus-based Pareto alliance conflict analysis apparatus can be found in the limitations of the consensus-based Pareto alliance conflict analysis method described above, and will not be repeated here. Each module in the aforementioned consensus-based Pareto alliance conflict analysis apparatus can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the corresponding operations of each module.

[0045] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a consensus-based Pareto alliance conflict analysis method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0046] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0047] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the following steps: To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

[0048] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

[0049] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0050] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0051] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application.

Claims

1. A consensus-based Pareto alliance conflict analysis method, characterized in that, The method includes: To construct a conflict graph model, we obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in an emergency rescue conflict. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing their own rescue strategy. The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. Under the condition of unknown adversary alliances in the focus alliance, we enumerate all feasible alliance schemes that satisfy the condition that a single adversary belongs to only one sub-alliance and that the adversary is fully involved. We construct the alliance domain consisting of the entire alliance of adversaries and the entire alliance set, and construct a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into credible adversary alliances and untrusted adversary alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. Based on the consensus-based Pareto alliance improvement matrix of the focus alliance, and the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, a consensus-based Pareto alliance stability determination rule under hybrid countermeasure behavior is constructed. Stability analysis is performed to obtain the equilibrium result of emergency rescue conflict. Finally, based on the equilibrium result, the causes and evolution of emergency rescue conflict are analyzed to assist decision-makers in making emergency rescue decisions.

2. The consensus-based Pareto alliance conflict analysis method according to claim 1, characterized in that, To obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships among decision-makers in an emergency rescue conflict, a conflict graph model is constructed, represented as follows: ;in, For decision-makers For the number of decision-makers and This includes both individual decision-makers and organizational decision-makers; This is the set of feasible states, indicating all feasible states formed by different combinations of rescue strategies adopted by the decision-maker. Indicates the first One state; For the set of state transition arcs, For decision-makers The set of all one-step unilateral moves. This represents the set of preference relationships corresponding to each decision-maker. Indicates decision-makers Binary preference information regarding state reflects the interests and objectives of decision-makers in emergency response conflicts, among which... Indicates decision-makers Preferring one of two states. Indicates decision-makers The preference for two states is the same.

3. The consensus-based Pareto alliance conflict analysis method according to claim 2, characterized in that, The method further includes: Decision-makers are constructed based on the conflict diagram model. The preference matrix and state transition matrix are expressed as follows: , , , as well as ;in, , and They represent the decision-makers. The preference improvement matrix, preference equivalence matrix, and preference inferiority matrix. and They represent the decision-makers. unilateral shift matrix and unilateral improvement matrix; Indicates decision-makers exist and Preference between two states ; Indicates decision-makers right and The two states have the same degree of preference; Indicates decision-makers exist and Preference between two states .

4. The consensus-based Pareto alliance conflict analysis method according to claim 3, characterized in that, The decision-maker set is divided based on alliance relationships, and a consensus-based Pareto alliance improvement matrix for focus alliances is constructed based on the alliance division results and conflict graph model, including: The set of decision-makers is partitioned based on alliance relationships, resulting in a set containing at least two alliances. And for the first Alliance When conducting the analysis, It is called the Focus League, while its opponents belong to the same league. The term "opponent alliance" refers to the total number of members in an opponent alliance. ;in, For decision-makers For set The total number of alliances in the country; Targeting the Focus Alliance and any state comparison pair ,according to Internal state Relative to state Number of decision-makers who share the same preference judgment and Total number of members The ratio, calculate Compare states Consent support for preference relationships , is represented as: ； in, Indicates about state Superior state Preference judgment, Indicates about state Equivalent to state Preference judgment, Indicates about state Inferior state Preference judgment; Based on approval ratings and Corresponding consensus threshold ,calculate The consensus-based Pareto improvement preference matrix is ​​expressed as: ； in, Used to measure preference state Superior state Does the member ratio meet the requirements? The consensus requires, Used to measure whether it is a focus alliance any decision-maker in Everyone believes Superior to or equivalent to ,symbol This represents the Hadamard product operator. Indicates decision-makers think Superior to or equivalent to The consensus threshold is determined based on the alliance's internal negotiation mechanism, alliance organizational rules, historical rescue decision-making patterns, or external input parameters. Further according to Consensus-based Pareto Improved Preference Matrix , build The consensus-based Pareto alliance improvement matrix is ​​expressed as: ； in, express Consensus-based Pareto alliance improvement set express Control in state Joint unilateral movement at the location, The methods of obtaining it include: For all Both are true; if and ,but ,and ;like , , ,but and The premise is ;in, Represents the union, express The set of all decision-makers who make the last move during the process of legal unilateral movement from one state to another is used. The set of feasible states Indicates decision-makers In state s A set of unilateral moves at a given location.

5. The consensus-based Pareto alliance conflict analysis method according to claim 4, characterized in that, The entire alliance and its domain are divided into credible adversary alliances and uncredible adversary alliances by considering differentiated responses to changes in rescue strategies for different focus alliances, including: Based on pre-defined behavioral constraints or historical game behavior data, we identify whether each adversary alliance considers its overall interests when implementing countermeasures. If an adversary alliance needs to satisfy a consensus-based Pareto superiority relationship between the countermeasure target state and the original state for the alliance as a whole when implementing countermeasures, then it is classified as a trustworthy adversary alliance. and define a trusted adversary alliance The consensus-based Pareto alliance improvement matrix adopted for countermeasures is as follows: Otherwise, classify it as an alliance of untrusted adversaries. and define untrusted adversary alliances The alliance movement matrix adopted for countermeasures is ;in, and These are the sets consisting of all trusted adversary alliances and all untrusted adversary alliances under the current analysis.

6. The consensus-based Pareto alliance conflict analysis method according to claim 5, characterized in that, Constructing a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain, including: All League Focus Alliance Focus Alliance The set of all alliance scenarios consisting of all opponents is called the alliance domain. ;in, For decision-makers; Building the entire alliance Consensus-based Hybrid Pareto Alliance Improvement Matrix , is represented as: ； Among them, for , ;for ,exist ,and , , Indicates from state Move to state The number of effective moves made across the entire alliance. Let be the total number of effective moves in the entire alliance; and for any three matrix A new operation is defined as ,That Item element is represented as ; For the entire alliance, its representation includes non-empty alliances. The set of all decision-makers in the alliance is the alliance situation for any type of opponent, and for any sub-alliance number in the entire alliance. , ,have ; The set of feasible states For any state comparison pair, Represents a matrix The sign function, Not included in the entire league The set of all other opposing alliances, symbol The difference operator for sets; Constructing the domain of alliances The consensus-based hybrid Pareto alliance improvement matrix is ​​represented as follows: : ； in, For the alliance domain, it represents the composition of the adversaries. A collection composed of all alliances For the first A full alliance.

7. The consensus-based Pareto alliance conflict analysis method according to claim 6, characterized in that, The consensus-based Pareto alliance stability determination rules under hybrid countermeasures include: Focus Alliance and ,state yes The consensus-based Pareto alliance Nash stability is achieved if and only if , recorded as ;in, It is a set of elements where all elements equal 1. dimensional vector, for A consensus-based Pareto alliance improvement matrix Indicates the first The item is 1 and the rest are 0. dimensional vector, express transpose, It is the set of all states that satisfy consensus-based Pareto-aligned Nash stability during a conflict; make and and given a 3D matrix ,state yes Consensus-based hybrid Pareto alliances (GMRs) are stable if and only if , recorded as , for Consensus-based Pareto non-improvement preference matrix This indicates that each item is 1. matrix, for The consensus-based Pareto improvement preference matrix, where the superscript T denotes matrix transpose. It is the set of all states that satisfy consensus-based Pareto-aligned GMR stability during a conflict; make and and given a 3D matrix ,in ,state It is an alliance Consensus-based hybrid Pareto alliance SMR is stable if and only if , recorded as ; for The matrix form of the joint unilateral movement, symbol This represents the Hadamard product operator. It is the set of all states that satisfy consensus-based Pareto-aligned SMR stability during a conflict; A strong equilibrium state is defined as a state that simultaneously satisfies consensus-based hybrid Pareto alliance Nash stability, consensus-based hybrid Pareto alliance GMR stability, and consensus-based hybrid Pareto alliance SMR stability.

8. A consensus-based Pareto alliance conflict analysis device, characterized in that, The device includes: The first module is used to obtain the set of decision-makers, feasible states, state transition arcs, and preference relationships of each decision-maker in emergency rescue conflicts, and to construct a conflict graph model. Here, a state is defined as the global situation of the emergency rescue scenario, and a state transition is defined as the process of global situation change caused by each decision-maker changing its own rescue strategy. The second module is used to divide the decision-maker set based on alliance relationships, and construct a consensus-based Pareto alliance improvement matrix for focus alliances based on the alliance division results and conflict graph model; where focus alliances refer to the alliances currently being analyzed after the alliance division. The third module is used to enumerate all feasible alliance schemes that satisfy the condition that a single opponent belongs to only one sub-alliance and that the opponent is fully involved, under the condition that the focus alliance has unknown opponents. It constructs the alliance domain composed of the entire alliance of opponents and the entire alliance set, and constructs a consensus-based hybrid Pareto alliance improvement matrix for the entire alliance and the alliance domain. Among them, the entire alliance and the alliance domain are divided into trusted opponent alliances and untrusted opponent alliances by considering the differentiated responses to the different rescue strategy changes of the focus alliance. The fourth module is used to construct consensus-based Pareto alliance stability judgment rules under hybrid countermeasure behavior based on the consensus-based Pareto alliance improvement matrix of the focus alliance, the consensus-based hybrid Pareto alliance improvement matrix of the whole alliance and the alliance domain, and to conduct stability analysis to obtain the equilibrium results of emergency rescue conflicts. Finally, based on the equilibrium results, the module analyzes the causes and evolution of emergency rescue conflicts, thereby assisting decision-makers in making emergency rescue decisions.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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