Method for studying and judging strategic situation based on conflict resolution model under multi-factor coupling condition

Abstract

A strategic situation research and judgment method based on a conflict resolution model under a multi-factor coupling condition belongs to the technical field of strategic situation research and judgment, and comprises the following steps: generating a feasible game state complete set and state transition among all feasible game states based on strategy set data of two battle parties, and generating an initial graph model; sorting declarations given by the two battle parties based on the strategy set data according to priorities to obtain a declaration sequence of the two battle parties; according to the order of the declarations, assigning and sorting coincidence conditions of the declarations according to the feasible game states, and establishing quantitative preference orders of the two battle parties on the feasible game states; and analyzing each feasible game state by using different stability conditions according to the quantitative preference sequence and the initial graph model, and iteratively calculating and identifying all the feasible game states meeting the stability conditions as a predicted conflict steady-state result set.

Description

Technical Field

[0001] This invention relates to a strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions, and belongs to the field of strategic situation assessment technology. Background Technology

[0002] Traditional strategic decision-making analysis methods are typically built upon the theoretical framework of game theory. They provide decision-makers with a basis for strategy selection in adversarial environments by constructing mathematical models such as Nash equilibrium and evolutionary stable strategies. Game theory, as a classic decision-making tool, can effectively characterize the interactive behavior of decision-makers, especially in scenarios of static games with complete information, where quantitative analysis of payoff matrices can yield theoretically complete optimal solutions. However, in strategic game analysis, traditional game theory methods are facing three core challenges:

[0003] First, the strong dependence on quantitative payoff data limits the application scope. Classic game theory models require clearly defining the strategy sets of each participant and accurately assigning utility values ​​to each game's endgame. However, in real-world strategic game scenarios, stakeholders often experience an information black box effect, and obtaining and quantifying key parameters presents insurmountable obstacles.

[0004] Secondly, there is a discrepancy between the rational man assumption and strategic decision-making practice. Traditional game theory takes perfectly rational decision-makers as a basic premise, requiring participants to possess unlimited computational power and perfect information processing capabilities. However, real-world strategic decisions are often made under conditions of bounded rationality, where decision-makers are constrained by multiple factors such as cognitive biases, group polarization effects, and information lags.

[0005] Furthermore, the modeling bottleneck of dynamic coupling of multiple factors is difficult to overcome. Modern strategic games exhibit obvious characteristics of complex systems, and the nonlinear interaction mechanisms between various elements lead to an exponential expansion of the game state space. The static payoff matrix and discrete strategy set used in traditional game theory are insufficient to characterize the dynamic evolution of the relationships between elements.

[0006] To address these shortcomings, existing research has attempted to overcome them using improved methods such as evolutionary game theory and fuzzy game theory. However, significant limitations remain when dealing with the coupling of high-dimensional, multimodal strategic elements. Current improvement schemes mostly focus on single-dimensional corrections and have not yet established a comprehensive analytical framework that can systematically integrate the network of strategic element relationships, dynamic game path deduction, and uncertainty resolution. Particularly in the processing of unstructured information, traditional methods cannot effectively integrate multi-source heterogeneous data such as expert experience, historical cases, and public opinion trends, resulting in a single-dimensional and time-sensitive strategic assessment. Summary of the Invention

[0007] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions. This method solves the inherent defects of traditional methods in terms of factor coupling analysis, imprecise benefit processing, and dynamic strategy optimization, and provides a brand-new methodological tool for decision support in complex strategic environments.

[0008] The technical solution of this invention is: Firstly, a method for strategic situation assessment based on a conflict resolution model under multi-factor coupling conditions, comprising:

[0009] Based on the strategy set data of the two opposing entities, a complete set of feasible game states and state transitions between all feasible game states are generated. Feasible game states are abstracted as nodes, and state transitions are abstracted as edges, generating an initial graph model to represent conflict events. The state transitions are generated by any opposing entity changing its strategy once. The strategy set data includes the actions, control methods, and resource allocation data of the two opposing parties.

[0010] Based on the strategy set data and the real-time state of the confrontation, the declarations given by the entities of both sides based on the strategy set data are sorted according to priority to obtain the declaration order of the entities of both sides.

[0011] Based on the stated declarations, scores are assigned to the conformity of the declarations according to the feasible game states, and a quantitative preference ranking of each opposing entity for the feasible game states is established.

[0012] Based on the quantified preference ranking and the initial graph model, each feasible game state is analyzed using different stability conditions. All feasible game states that satisfy the stability conditions are iteratively calculated and identified as the predicted set of conflict steady-state results.

[0013] The set of conflict steady-state results is output to the host computer visualization interface to display the conflict steady-state result prediction to the user in a visual manner, so as to provide the user with strategy suggestions.

[0014] Furthermore, the method for establishing the preference ranking of feasible game states for each opposing side is the strategy priority ranking method.

[0015] Furthermore, the stability criteria include Nash stability, general suprarational stability, symmetric suprarational stability, and sequence stability.

[0016] Furthermore, the scoring method is as follows: Where i is the index of the two opposing sides, and r is the number of strategy declarations made by opposing side i. For the r-th declaration by player i in a battle, T represents a logically true statement; F represents a logically false statement. The game state is based on the r-th declaration of both players. The score is s, where s represents the stable state of both sides in the battle.

[0017] Furthermore, the complete set of feasible game states includes the set of game states obtained by arranging and combining all game states through strategy set data and excluding infeasible game states that do not conform to real-world logic or have strategic conflicts.

[0018] Furthermore, the state transition includes the ability of a conflict event to transition from one feasible game state to another adjacent feasible game state in accordance with the direction of state transition in the initial graph model.

[0019] Furthermore, the statement includes a combination of strategies and logical symbols; the logical symbols include AND, OR, NOT, if, and if and only if.

[0020] Furthermore, the quantitative preference ranking includes each player ranking all feasible game states according to their own preferences, where the relationship between two adjacent feasible game states includes being better than or equal to each other.

[0021] Furthermore, the equilibrium solution under any stability criterion is a feasible game state that satisfies the stability criterion for all opposing sides.

[0022] Secondly, a strategic situation assessment device based on a conflict resolution model under multi-factor coupling conditions includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: when the processor executes the computer program, it implements the steps of the strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions.

[0023] The advantages of this invention compared to the prior art are:

[0024] Based on the graphical model theory GMCR, this invention uses a combination of qualitative and quantitative methods to analyze the process and predict the outcome of conflict situations through logical analysis of many real-world conflict problems that are difficult to describe quantitatively, thereby providing decision-makers with certain decision-making basis. Attached Figure Description

[0025] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0026] Figure 1 This is a schematic diagram of the conflict analysis process;

[0027] Figure 2 A schematic diagram illustrating the logical relationships between the four types of stability;

[0028] Figure 3 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0029] To better understand the above technical solutions, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solutions of the present invention, rather than limitations on the technical solutions of the present invention. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0030] The following description, in conjunction with the accompanying drawings, provides a more detailed explanation of the strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions provided by the embodiments of the present invention. Specific implementation methods may include:

[0031] Based on the strategy set data of the two opposing entities, a complete set of feasible game states and state transitions between all feasible game states are generated. Feasible game states are abstracted as nodes, and state transitions are abstracted as edges, generating an initial graph model to represent conflict events. The state transitions are generated by any opposing entity changing its strategy once. The strategy set data includes the actions, control methods, and resource allocation data of the two opposing parties.

[0032] Based on the strategy set data and the real-time state of the confrontation, the declarations given by the entities of both sides based on the strategy set data are sorted according to priority to obtain the declaration order of the entities of both sides.

[0033] Based on the stated declarations, scores are assigned to the conformity of the declarations according to the feasible game states, and a quantitative preference ranking of each opposing entity for the feasible game states is established.

[0034] Based on the quantified preference ranking and the initial graph model, each feasible game state is analyzed using different stability conditions. All feasible game states that satisfy the stability conditions are iteratively calculated and identified as the predicted set of conflict steady-state results.

[0035] The set of conflict steady-state results is output to the host computer visualization interface to display the conflict steady-state result prediction to the user in a visual manner, so as to provide the user with strategy suggestions.

[0036] In the solutions provided in the embodiments of the present invention, such as Figure 1 In view of the characteristics of multiple influencing factors such as the strategies that may be adopted in the process of conflict evolution, the equilibrium state of reaching a compromise, and the evolution path of the game state, this paper proposes a strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions, based on the principle of decision analysis that combines qualitative and quantitative methods according to game theory.

[0037] The specific technical solution is as follows:

[0038] 1) Identify decision-makers and strategies

[0039] The strategy prioritization method involves decision-makers making statements of current strategic options and ranking these statements according to priority, thus obtaining the decision-maker's ranking. Each statement consists of strategic options and logical symbols. These logical symbols and their meanings include: A and B represent two strategies; the symbols "-", "&", and "|" represent "NOT", "AND", and "OR" relationships, respectively; and the symbols "IF" and "IFF" represent the conditional form "if" and the two-conditional form "if and only if", respectively.

[0040] 2) Define the game state

[0041] All feasible game states formed by combining the strategies of all parties are listed. Based on the decision-maker's strategy set data, a complete set of game states composed of different strategy combinations and all potential state transitions are generated. Combining the relevant definitions of graph models, game states are abstracted as nodes, and state transitions caused by any decision-maker changing their strategy once are abstracted as edges, generating an initial graph model to represent conflict events.

[0042] 3) Establish a preference structure

[0043] Based on the preferences of each party for different game states, a preference ranking is established, which mainly includes the direct state ranking method, the strategy weighted average method, and the strategy priority ranking method.

[0044] 4) Stability analysis

[0045] In dynamic games, mutual influence and constraints exist, and unilateral moves by decision-makers can be countered by other decision-makers. Through stability analysis, decision-makers can analyze each game state based on GMCR data using different stability criteria (such as Nash stability, GMR stability, etc.). This analysis examines the moves they can make to achieve a better preferred state during game evolution and the potential countermeasures they might face, thereby identifying steady states where decision-makers have no incentive to continue moving under a given behavioral pattern. If all decision-makers achieve stability after reaching a certain state, it is defined as an equilibrium state representing a potential compromise solution.

[0046] 5) Sensitivity analysis

[0047] To account for the impact of different parameter variations on the structural data and decision-maker preference data of the conflict resolution diagram model, a parameter sensitivity analysis can be performed after the stability analysis to draw conclusions.

[0048] Conflict resolution graph models are game theory-based decision analysis tools that combine qualitative and quantitative methods, and are widely used for resolving and predicting multi-party conflicts. These models represent different states, participating players, and their strategy choices in a conflict using a graph theory structure. They can systematically analyze the preferences and behavioral interactions of the conflicting parties, helping to identify the evolution path of the conflict and the eventual stable solution.

[0049] like Figure 3 The main calculation process of this model includes the following steps:

[0050] (1) Identify the decision-maker and strategy options;

[0051] (2) Calculate feasible game states and generate initial graph models of conflict;

[0052] (3) Calculate the preference data of each decision-maker for the game state;

[0053] (4) Calculate the stable state that the conflict may reach, i.e. the equilibrium solution of the conflict.

[0054] Theoretically, in a conflict event, if there are k strategies, and for each strategy, the decision-maker can choose whether to adopt that strategy, then the theoretical number of states is:

[0055] m=2 k

[0056] In the formula: m—number of theoretical game states; k—number of decision-makers' strategy options.

[0057] However, not all states are conflicting feasible states. After eliminating infeasible states, we obtain the set of feasible game states.

[0058] Graph model calculation: State transitions represent how a decision-maker can move from the current state to another state in one step by unilaterally changing their strategy. Theoretically, there should be two state transitions between any two game states where only one side's strategy differs. However, not all state transitions conform to real-world logic. After eliminating infeasible state transitions, the game states are abstracted as nodes, and state transitions are abstracted as edges, resulting in an initial graph model.

[0059] Preference data calculation: The policy priority ranking method is used to solve the preference data. This method involves the decision-maker giving a statement of the current policy and ranking the statements according to their priority. Each statement consists of a policy and logical symbols ("-", "&", "|", "IF", and "IFF").

[0060] In the order of declarations, the earlier the declaration appears, the greater its priority. Suppose decision-maker i has l policy declarations, let... (Sorted from best to worst) is the order of policy declarations given by decision-maker i. For each state s∈S, in each declaration by decision-maker i... Each location must be assigned a truth value, either T or F. If This indicates that state s satisfies the r-th statement of decision-maker i. if This indicates that state s does not satisfy the r-th statement of decision-maker i.

[0061] The game states can be scored based on the strategy declaration order set, and the preference of decision-maker i for each state can be obtained by sorting the states according to their scores. The scoring rules are as follows:

[0062]

[0063] In the formula: i—decision-maker number; r—number of strategy statements made by decision-maker i; —The r-th statement by decision-maker i; T—short for “True”, indicating that the logic is true; F—short for “False”, indicating that the logic is false; —The game state is based on the r-th statement made by decision-maker i. The score.

[0064] Then the score of decision-maker i for state s∈S is

[0065]

[0066] In the formula: Ψ i (s) — The game state score of decision-maker i for game state s.

[0067] like Figure 2 Stability analysis calculations: In GMCR theory, commonly used stability factors include Nash stability, General Metarationality (GMR), Symmetric Metarationality (SMR), and Sequential Stability (SEQ). These four basic stability factors consider whether decision-makers are willing to transition to a better state than their current one, whether adversaries only consider states advantageous to themselves when retaliating, and the further actions taken after an adversary's retaliation. Therefore, these four basic stability factors reflect the conservative or aggressive behavioral characteristics of decision-makers.

[0068] For decision-makers i∈N and state s∈S, if the following conditions are met... For decision-maker i, state s is the Nash stable state of decision-maker i, denoted as . If state s is Nash stable for both decision-makers i and j, then state s is called a conflicting Nash equilibrium solution.

[0069] Where: i—decision-maker number; —The improved state set of decision-maker i, representing the set of states that decision-maker i can reach in one step from state s and is superior to state s.

[0070] For decision-makers i,j∈N, and states s∈S, for any one There exists at least one s2∈R j (s1), such that s > ~ i s2, then for decision-maker i, state s is the GMR stable state of decision-maker i, denoted as If state s is GMR stable for both decision-makers i and j, then state s is called a conflicting GMR equilibrium solution.

[0071] Where: i, j — decision-maker serial numbers; —The improved state set of decision-maker i, representing the set of states that decision-maker i can reach in one step from state s and that are superior to state s; R j (s1) — The set of reachable states for decision-maker j, representing the set of states that decision-maker j can reach in one step from state s1;

[0072] For decision-makers i,j∈N, and states s∈S, for any one There exists at least one s2∈R j (s1), such that s > ~ i s2; and for any s3∈R i (s2), all have s>~ i s3, then for decision-maker i, state s is the SMR stable state of decision-maker i, denoted as If state s is SMR stable for both decision-makers i and j, then state s is called a conflicting SMR equilibrium solution.

[0073] For decision-makers i,j∈N, and states s∈S, for any one At least one exists Makes s > ~ i s2, then for decision-maker i∈N, state s is the SEQ stable state of decision-maker i, denoted as If state s is SEQ stable for both decision-makers i and j, then state s is called a conflicting SEQ equilibrium solution.

[0074] The calculation rules are as follows:

[0075] The number, names, and strategy options of decision-makers are determined based on the conflict events. During the process, it is necessary to determine whether the number of decision-makers is greater than 1 and whether all decision-makers have at least one strategy option. If not, the analysis cannot be performed.

[0076] After generating theoretical game states based on the number of strategy options and removing infeasible game states, a set of feasible game states is obtained. Here, it is necessary to determine whether the removed infeasible states meet the operator's requirements. After obtaining the set of feasible game states, state transitions between the two states are assigned according to different unilateral strategy schemes, and infeasible state transitions are removed. Here, it is necessary to determine whether the removed infeasible state transitions meet the operator's requirements, and a conflict event graph model is generated.

[0077] Input the strategy statements of each decision-maker, then determine how well each game state conforms to the strategy statements and assign scores to rank them, to obtain the preference data of each decision-maker for the game state.

[0078] Finally, by combining the conflict event graph model and preference data, we determine the compliance of each feasible game state with the four stability conditions and derive the possible steady-state, i.e., the set of equilibrium solutions, for the future conflict. This concludes the conflict resolution graph model analysis.

[0079] This invention provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform... Figure 3 The method described.

[0080] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0081] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0085] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions, characterized in that, include: Based on the strategy set data of the two opposing entities, a complete set of feasible game states and state transitions between all feasible game states are generated. Feasible game states are abstracted as nodes and state transitions are abstracted as edges to generate an initial graph model to represent conflict events. The state transition is generated by any combat entity changing its strategy once; the strategy set data includes the actions, control methods, and resource allocation data of both combatants. Based on the strategy set data and the real-time state of the confrontation, the declarations given by the entities of both sides based on the strategy set data are sorted according to priority to obtain the declaration order of the entities of both sides. Based on the stated declarations, scores are assigned to the conformity of the declarations according to the feasible game states, and a quantitative preference ranking of each opposing entity for the feasible game states is established. Based on the quantified preference ranking and the initial graph model, each feasible game state is analyzed using different stability conditions. All feasible game states that satisfy the stability conditions are iteratively calculated and identified as the set of predicted conflict steady-state results. The set of conflict steady-state results is output to the host computer visualization interface to display the conflict steady-state result prediction to the user in a visual manner, so as to provide the user with strategy suggestions.

2. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The method for establishing the preference ranking of feasible game states for each opposing side is the strategy priority ranking method.

3. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The stability criteria include Nash stability, general suprarational stability, symmetric suprarational stability, and sequence stability.

4. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The scoring method is as follows: Where i is the index of the two opposing sides, and r is the number of strategy declarations made by opposing side i. For the r-th declaration by player i in a battle, T represents a logically true statement; F represents a logically false statement. The game state is based on the r-th declaration of both players. The score is s, where s represents the stable state of both sides in the battle.

5. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The complete set of feasible game states includes the set of game states obtained by arranging and combining all game states through the strategy set data, and excluding infeasible game states that do not conform to real-world logic or have strategic conflicts.

6. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The state transition includes the ability of a conflict event to transition from one feasible game state to another adjacent feasible game state in accordance with the direction of state transition in the initial graphical model.

7. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The statement includes a combination of strategies and logical symbols; the logical symbols include AND, OR, NOT, if, and if and only if.

8. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, The quantitative preference ranking includes each player ranking all feasible game states according to their own preferences, where the relationship between two adjacent feasible game states is either better than or equal to.

9. The strategic situation assessment method based on a conflict resolution model under multi-factor coupling conditions as described in claim 1, characterized in that, An equilibrium solution under any stability criterion is a feasible game state that satisfies the stability criterion for all opposing sides.

10. A strategic situation assessment device based on a conflict resolution model under multi-factor coupling conditions, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 9.

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