Agent-based wargaming method

Abstract

This invention discloses a wargaming method based on intelligent agents, comprising the following steps: setting wargaming parameters including terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters of the combat area; constructing a wargaming model including a parameter correlation mapping system, a dynamic computing engine, and a feedback iteration mechanism; inputting the wargaming parameters into the wargaming model and conducting wargaming in stages to obtain wargaming results; analyzing and optimizing the wargaming results, collecting various data during the wargaming process, analyzing the advantages and disadvantages of the combat plan, and optimizing the plans for troop deployment, weapon use, and tactical coordination; verifying and iterating the wargaming, repeating the above wargaming steps, verifying the feasibility and stability of the optimized plan through multiple rounds of wargaming, and forming a final island attack wargaming report.

Description

Technical Field

[0001] This invention relates to a wargaming method based on intelligent agents, specifically an island warfare simulation method based on intelligent agents. It is applicable to the simulation, tactical verification, and scheme optimization of amphibious joint operations, and can accurately simulate the entire process of island attack operations, providing data support and scheme reference for operational command and decision-making. Background Technology

[0002] Island assault operations are a complex form of amphibious joint operations, involving coordination among multiple services—sea, land, and air—and encompassing key aspects such as troop deployment, beachhead assault, and deep penetration. They are highly risky and difficult to command due to the influence of terrain, climate, and the deployment of enemy and friendly forces and equipment. Current operational simulation methods suffer from the following shortcomings: First, they fail to fully consider the unique characteristics of island assault operations, resulting in insufficient accuracy in simulating core scenarios such as amphibious deployment, beach defense, and terrain adaptation. Second, the parameters for enemy and friendly forces and weaponry are set too generally during simulations, lacking specific and quantifiable assumptions, leading to significant discrepancies between simulation results and actual combat scenarios. Third, the simulation logic is too simplistic, failing to achieve coordinated action across multiple factors such as terrain, climate, weapon performance, and personnel deployment, making it difficult to comprehensively verify the feasibility and rationality of the operational plan.

[0003] Therefore, there is an urgent need for a simulation method that can combine specific assumptions, achieve multi-factor synergy, and accurately simulate the entire process of island attack operations. This method would address the problems of existing simulation methods being unreliable, inaccurate, and having limited reference value, and provide reliable support for the formulation, optimization, and tactical training of island attack operation plans. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a wargaming method based on intelligent agents. By setting specific assumptions about personnel, weapons, equipment, terrain, and climate on both sides, a multi-factor collaborative simulation model is constructed to achieve accurate simulation of the entire process of island attack operations, improve the authenticity and reference value of the simulation results, and provide a scientific basis for combat command and decision-making.

[0005] The present invention provides an agent-based wargaming method for island warfare simulation, comprising:

[0006] Intelligent agents are used to set inference parameters, including terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters of the combat area;

[0007] Construct a deductive model that includes a parameter correlation mapping system, a dynamic calculation engine, and a feedback iteration mechanism;

[0008] The simulation parameters are input into the simulation model, and the simulation is carried out in stages, including the combat process of "pre-war preparation - troop deployment - beachhead assault - in-depth advance - combat cleanup". The simulation is carried out in stages, and the combat losses, advance efficiency and target achievement status of each stage are calculated in real time. The simulation parameters are dynamically adjusted to obtain the simulation results.

[0009] The simulation results are analyzed and optimized by collecting various data during the simulation process, analyzing the advantages and disadvantages of the combat plan, and optimizing the plans for troop deployment, weapon use, and tactical coordination.

[0010] The simulation and iteration process involves repeating the above simulation steps and conducting multiple rounds of simulations to verify the feasibility and stability of the optimized plan, ultimately forming the final island attack operation simulation report.

[0011] Preferably, the phased simulation includes: conducting phased simulations according to the operational process of "pre-war preparation - troop deployment - beachhead assault - in-depth advance - combat cleanup", calculating the combat losses, advance efficiency, and target achievement status of each phase in real time, and dynamically adjusting the simulation parameters.

[0012] Preferably, the parameter association mapping system is created in the following manner:

[0013] Establish quantitative sub-parameters for terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters;

[0014] Determine the rules governing the influence between quantized sub-parameters;

[0015] Determine the derived parameters related to the quantized sub-parameters based on the influence rules among the quantized sub-parameters;

[0016] Establish a mapping relationship between one or more quantization sub-parameters and related derived parameters.

[0017] Preferably, the quantifiable sub-parameters of terrain parameters include shore slope, water depth, and vegetation coverage; the quantifiable sub-parameters of climate parameters include wind speed, wave height, and visibility; and the quantifiable sub-parameters of weapon performance parameters include amphibious tank water speed and fire accuracy.

[0018] Preferably, the rules governing the influence between quantized sub-parameters include, but are not limited to:

[0019] Wave height correlates with a decrease in the speed of the air-cushioned landing craft.

[0020] High vegetation coverage reduces the speed of personnel advancement and increases the success rate of ambushes by the defending side.

[0021] Preferably, by utilizing the established mapping relationship between quantitative sub-parameters including beach slope and wind speed, quantitative parameters for fire strike accuracy, and derived parameters including landing efficiency and fire strike accuracy, derived parameters including landing efficiency and fire strike accuracy are obtained; the derived parameters are then used to calculate the results of each simulation stage, including troop deployment and beach assault.

[0022] Preferably, the dynamic calculation engine performs the following operations: inputting various quantifiable sub-parameters into the engine, assigning each sub-parameter a unique identifier and quantization weight; when a sub-parameter changes, the engine automatically triggers a correlation retrieval to extract all correlation rules corresponding to that parameter; dynamically adjusting the calculation function of the relevant inference process based on the quantization weight; and synchronously updating the derived values ​​of the correlation parameters.

[0023] Preferably, the feedback iteration mechanism includes: during the simulation process, after each type of parameter changes, the engine immediately outputs the adjusted simulation data and synchronously feeds it back to all related simulation stages.

[0024] Preferably, the feedback iteration mechanism further includes: combining data from multiple rounds of simulations to automatically optimize parameter correlation weights, ensuring that parameter linkage is more in line with actual combat logic.

[0025] The present invention has the following beneficial technical effects: by using a multi-factor collaborative simulation model, it realizes the dynamic linkage of multiple factors such as terrain, climate, weapon performance, and personnel deployment, which can accurately simulate the entire process of island attack operations and make the simulation results more realistic. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a wargaming method based on intelligent agents. Detailed Implementation

[0027] The present invention provides a wargaming method based on intelligent agents for island warfare simulation, as follows: Figure 1 As shown, the process includes: using an intelligent agent to set simulation parameters, including terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters of the combat area; constructing a simulation model including a parameter correlation mapping system, a dynamic computing engine, and a feedback iteration mechanism; inputting the simulation parameters into the simulation model and conducting simulations in stages to obtain simulation results; analyzing and optimizing the simulation results, collecting various data during the simulation process, analyzing the advantages and disadvantages of the combat plan, and optimizing the plans for troop deployment, weapon use, and tactical coordination; and verifying and iterating the simulation by repeating the above simulation steps and verifying the feasibility and stability of the optimized plan through multiple rounds of simulations, thus forming a final island attack operation simulation report. The intelligent agent used in this invention can be software, hardware, or a comprehensive system.

[0028] The phased simulation of this invention includes: conducting phased simulations based on the operational process of "pre-war preparation - troop deployment - beachhead assault - in-depth advance - combat cleanup", calculating operational losses, advance efficiency, and target achievement status in real time for each phase, and dynamically adjusting simulation parameters.

[0029] In the agent-based wargaming method of the present invention, a parameter association mapping system is created in the following ways: quantified sub-parameters of terrain parameters, quantified sub-parameters of climate parameters, quantified sub-parameters of personnel deployment parameters, and quantified sub-parameters of weapon performance parameters are established; the influence rules between quantified sub-parameters are determined; the derived parameters related to the quantified sub-parameters are determined according to the influence rules between quantified sub-parameters; and a mapping relationship between one or more quantified sub-parameters and related derived parameters is established.

[0030] The quantifiable sub-parameters of the terrain parameters of this invention include shore slope, water depth, and vegetation coverage; the quantifiable sub-parameters of the climate parameters include wind speed, wave height, and visibility; and the quantifiable sub-parameters of the weapon performance parameters include amphibious tank water speed and fire accuracy.

[0031] The influence rules between the quantitative sub-parameters of this invention include, but are not limited to: wave height associated with a decrease in the speed of the air-cushioned landing craft; high vegetation coverage associated with a decrease in the advance speed of personnel and an increase in the success rate of ambushes by the defending side.

[0032] This invention utilizes the established mapping relationship between quantitative sub-parameters including beach slope and wind speed, quantitative parameters for fire strike accuracy, and derived parameters including landing efficiency and fire strike accuracy to obtain derived parameters including landing efficiency and fire strike accuracy; and uses the derived parameters to calculate the results of various simulation stages including troop deployment and beachhead assault.

[0033] This invention achieves the following operations through a dynamic calculation engine: various quantifiable sub-parameters are entered into the engine, and each sub-parameter is assigned a unique identifier and quantification weight; when a sub-parameter changes, the engine automatically triggers a correlation retrieval to extract all correlation rules corresponding to that parameter; based on the quantification weight, the calculation function of the relevant inference process is dynamically adjusted; and the derived values ​​of the correlation parameters are updated synchronously.

[0034] The feedback iteration mechanism of the present invention includes: during the simulation process, after each type of parameter changes, the engine immediately outputs the adjusted simulation data and synchronously feeds it back to all related simulation stages.

[0035] The feedback iteration mechanism of this invention also includes: combining data from multiple rounds of simulations to automatically optimize the parameter association weights, ensuring that parameter linkage is more in line with actual combat logic.

[0036] The specific embodiments of the present invention for achieving multi-factor synergistic linkage and parameter correlation adjustment in the inference model are as follows:

[0037] The core technology of this invention is to construct a three-in-one implementation logic of "parameter association mapping + dynamic calculation engine + feedback iteration mechanism".

[0038] To construct a parameter correlation mapping system, first clarify the correlation relationships among four main categories of parameters: terrain, climate, weapon performance, and personnel deployment, and then establish a mapping table:

[0039] Basic correlation definition: Each type of parameter is broken down into quantifiable sub-parameters (e.g., terrain is broken down into shore slope, water depth, and vegetation coverage; climate is broken down into wind speed, wave height, and visibility), and the influence rules between sub-parameters are clarified (e.g., "wave height > 1.2 meters" will be associated with "air cushion landing craft speed reduced by 20%", and "vegetation coverage > 60%" will be associated with "personnel advance speed reduced by 30% + defender's ambush success rate increased by 15%").

[0040] Hierarchical correlation division: The correlation is based on "basic parameters → derived parameters → simulation results". Basic parameters (such as terrain slope and wind speed) directly affect derived parameters (such as landing efficiency and fire strike accuracy). The derived parameters then affect the calculation results of each simulation stage (troop deployment, beachhead assault, etc.), forming a closed-loop correlation chain.

[0041] Dynamic calculation engine construction, parameter input and initialization: Enter the specific parameters (such as beach slope of 5°-10°, wind speed of 5-8 m / s, amphibious tank water speed of 10km / h, etc.) into the engine, and assign each parameter a unique identifier and quantitative weight (such as the influence of terrain on beach assault weight of 30%, climate weight of 20%).

[0042] Real-time linkage calculation logic: When a certain parameter changes (such as wind speed increasing from level 3 to level 5), the engine automatically triggers correlation retrieval to extract all correlation rules corresponding to that parameter (such as when wind speed > 8 m / s, the success rate of helicopter take-off and landing decreases by 40%, and the damage of air-cushioned landing craft increases by 15%); based on preset weights, the calculation functions of related simulation links are dynamically adjusted (such as troop deployment time = basic deployment time ÷ (1 - wind speed influence coefficient), equipment damage = basic damage × (1 + wind speed influence coefficient)); the derived values ​​of correlation parameters are updated synchronously (such as the increase in wind speed causing delay in helicopter support, which in turn leads to a decrease in the fire suppression efficiency of beach assault, and finally adjusts the beach breakthrough time).

[0043] Feedback and iteration mechanism, real-time feedback: During the simulation, after each type of parameter changes, the engine immediately outputs adjusted simulation data (such as personnel losses and advance speed) and synchronously feeds it back to all related simulation stages to ensure data consistency (e.g., increased water depth in shallow areas affects both the delivery efficiency of air-cushioned landing craft and underwater obstacle removal time, thus requiring synchronous adjustments to the beachhead assault progress). Adaptive optimization: Combining data from multiple simulations, the system automatically optimizes parameter correlation weights (e.g., if multiple simulations reveal that "anti-tank missile deployment" has a greater impact on beachhead losses, its correlation weight can be dynamically increased), ensuring that parameter linkage more closely aligns with actual combat logic.

[0044] Taking "the slope of the beach increases from 7° to 12°" (a change in topographic parameters) as an example, the linkage process is as follows:

[0045] The engine detected a change in the slope parameter and retrieved the correlation rule: when the slope is greater than 10°, the amphibious tank's water speed decreases by 15% and the beachhead breakthrough resistance increases by 25%.

[0046] Dynamic adjustments were made to troop deployment: the time for amphibious tanks to reach the beachhead was extended by 15%, the difficulty of docking hovercraft increased, and equipment losses increased by 10%.

[0047] The beachhead assault phase was adjusted simultaneously: the breakthrough time was extended by 25%, casualties among the attacking personnel increased by 20%, which in turn affected the start time of the advance and the logistical supply requirements.

[0048] All related data are updated in real time to ensure that the simulation results are consistent with the logic of parameter changes.

[0049] A key aspect of this invention lies in setting specific and quantifiable deduction assumptions to ensure the authenticity and relevance of the deduction process. The specific assumptions are as follows:

[0050] The operational target is set as a medium-sized island (hereinafter referred to as "target island"). The island is located in near-shore waters, about 30-40 kilometers from our coast, with a total area of ​​about 80 square kilometers and complex and diverse terrain. The specific settings are as follows:

[0051] Beach Topography: The main landing area is on the east side of the island, with a beach length of about 8 kilometers. It is mainly sandy mudflats with a gentle slope (5°-10°), suitable for amphibious armored vehicle landings. However, there are shallow waters (0.5-2 meters deep) 1-2 kilometers from the shore, and underwater obstacles are deployed in some areas. The west and north sides are rocky coastlines with steep slopes (over 30°) and many cliffs, making them unsuitable for large-scale landings. The south side has a small bay with a water depth of 3-5 meters, which can be used as an auxiliary landing point. However, the bay entrance is narrow and easily blocked by enemy fire.

[0052] Inland terrain: The central part of the island consists of low hills (100-300 meters above sea level) with a vegetation coverage of about 60%, mostly shrubs and low trees. The limited visibility makes it unfavorable for the advance of mechanized forces, but suitable for the defenders to deploy covertly and ambush. The area around the hills is a plain (below 50 meters above sea level) with small villages and simple roads, which can be used as temporary strongholds for troop assembly and logistical support. There is a small airport (1200-meter runway) in the northeast of the island, which can take off and land light fighter jets and helicopters, providing air support for the defenders. There is a small port in the southwest, which can dock small warships and transport ships.

[0053] Defensive fortifications: The defenders deployed anti-tank ditches, barbed wire, and minefields (density of approximately 0.8 mines per square meter) on the main landing beach on the east side. They also constructed permanent fortifications (concrete bunkers and underground shelters) on the hilly high points and around the airport and port. Roadblocks and blasting points were set up at the main roads and bridges, forming a multi-layered and three-dimensional defense system.

[0054] The operational period is set for April and May each year (excluding typhoon season and peak monsoon season), within a subtropical monsoon climate zone. Specific climatic conditions are set as follows to ensure that the impact of climatic factors on the operation can be quantified and simulated:

[0055] Temperature: The average daytime temperature is 20-25℃, and the average nighttime temperature is 15-18℃. The temperature difference is small, which has little impact on personnel combat and weapon performance.

[0056] Wind force: Average wind force 3-4, mainly southeasterly, wind speed 5-8 m / s, with little impact on amphibious ship navigation and helicopter take-off and landing, and only a slight impact on the navigation stability of small landing craft.

[0057] Precipitation: No significant precipitation is expected during the simulation period. Visibility will be good (10-15 km during the day and 5-8 km at night), which is conducive to aerial reconnaissance, fire strikes and troop deployment.

[0058] Sea conditions: Nearshore waters have wave heights of 0.5-1.2 meters, with no reefs or strong currents, allowing amphibious landing craft and hovercraft to navigate and conduct beach landings normally. Underwater visibility is 3-5 meters, facilitating underwater obstacle removal operations.

[0059] Assuming the attacking force's strength and weaponry, the attacking force is an amphibious joint operations force with a total strength of 12,000 personnel, composed of army amphibious mechanized units, naval vessels, air force aviation units, special forces, and logistics support units. Specific troop strength and weaponry are set as follows, with all weapon performance parameters based on existing mainstream equipment to ensure rationality:

[0060] Troop deployment: Army amphibious mechanized forces: 8,000 personnel, organized into 2 amphibious mechanized brigades, each brigade consisting of 3 amphibious mechanized battalions, 1 artillery battalion, and 1 air defense battalion, mainly responsible for beachhead assault, in-depth advance, and island control.

[0061] Naval vessel force: 2,000 personnel, organized into one amphibious combat formation, mainly responsible for troop deployment, maritime blockade, air defense and anti-ship, and fire support missions;

[0062] Air Force Aviation Unit: 1,200 personnel, organized into 1 fighter regiment, 1 attack aircraft regiment, and 1 helicopter regiment, mainly responsible for air superiority struggle, aerial reconnaissance, close air support, and airborne delivery missions;

[0063] Special Forces: 500 personnel, organized into one special operations battalion, mainly responsible for pre-battle reconnaissance, infiltration behind enemy lines, sabotage of key enemy facilities, and guiding fire strikes;

[0064] Logistics support unit: 300 people, mainly responsible for material supply, medical rescue, equipment maintenance and communication support.

[0065] The attacking side's weapons, equipment, and performance parameters are as follows:

[0066]

[0067] Assumptions regarding the defending force's strength and weaponry:

[0068] The defending force is the island defense unit, with a total strength of 6,000 personnel, composed of army defense forces, naval coastal defense forces, air force air defense forces, and logistics support forces. They will construct a defense system based on the island's terrain. Specific troop strength and weaponry are as follows:

[0069] Troop deployment: Army defense forces: 4,000 personnel, organized into 2 defense brigades, each brigade consisting of 3 defense battalions, 1 artillery battalion, and 1 anti-tank battalion, mainly responsible for beach defense, ambush in hilly areas, and defense in depth, with key deployments on the eastern landing beach, hilly high points, and around the airport and port; Navy coastal defense forces: 1,000 personnel, organized into 2 coastal defense battalions, mainly responsible for coastal anti-ship, underwater defense, and harbor blockade, deployed along the coastline around the island and at the entrance to the harbor; Air force air defense forces: 600 personnel, organized into 1 air defense regiment, mainly responsible for island air defense, deployed around the airport, port, and command center; Logistics support forces: 400 personnel, mainly responsible for material supply, medical rescue, equipment maintenance, and communication support, deployed in concealed areas behind the hills in the central part of the island.

[0070] The defending side's weapons, equipment, and performance parameters are as follows:

[0071]

[0072] The deductive model of this invention is constructed based on the logic of multi-factor synergy and linkage. Combined with the above assumptions, it focuses on achieving the following core functions:

[0073] Troop deployment simulation: Simulates the troop deployment process of amphibious ships, hovercraft, and helicopters. Combines sea state, wind force and other climate parameters to calculate deployment time, deployment efficiency and personnel and equipment losses. Considers the interception impact of enemy coastal defense missiles and coastal defense artillery, and dynamically adjusts the deployment route and deployment timing.

[0074] Beachhead assault simulation: Simulates the process of the attacking amphibious forces' beach landing, and calculates the beachhead breakthrough time and personnel and equipment losses by combining parameters such as beach terrain, underwater obstacles, and enemy fortifications. Simulates the confrontation between the attacking force's fire suppression (rocket artillery, howitzers, and air strikes) and the defending force's defensive firepower (coastal artillery and anti-tank missiles).

[0075] In-depth advance simulation: Simulates the process of the attacking force advancing into the depth of the island after breaking through the beachhead. Combining terrain parameters such as hills and plains, it simulates the confrontation between the defending force's ambush and anti-tank operations and the attacking force's mechanized advance and air support, and calculates the advance speed, target achievement status and combat losses.

[0076] Air defense and anti-ship simulation: Simulates the confrontation between the attacking air force and navy and the defending air defense forces and coastal defense forces. Combines the performance parameters of weapons and equipment to calculate the struggle for air and sea control, and simulates the interception efficiency and strike effect of missiles and cannons.

[0077] Logistics support simulation: Simulate the process of supplying materials, providing medical care, and repairing equipment for the attacking side. Combine terrain and climate parameters to calculate supply efficiency, casualty treatment rate, and equipment repair rate, and analyze the impact of logistics support on the combat process.

[0078] Parameter linkage adjustment: During the simulation, parameters such as terrain, climate, weapon performance, and personnel deployment are interrelated. When a parameter changes, the calculation results of the relevant simulation links are automatically adjusted to ensure the realism and consistency of the simulation.

[0079] Example 1

[0080] Step 1, Set the basic assumptions for the deduction:

[0081] Topographical parameters: the eastern shore slope is 7°, the shallow water depth is 1.2 meters, the hill elevation is 200 meters, the vegetation coverage is 60%, and the airport runway length is 1200 meters.

[0082] Climate parameters: Daytime temperature 22℃, wind force 3, southeast wind, wind speed 6 m / s, wave height 0.8 m, visibility 12 km;

[0083] Attacking force's core parameters: 2 amphibious assault ships, 60 amphibious main battle tanks, 36 fighter jets, and a total force of 12,000 personnel;

[0084] The defending side's core parameters include: 18 shore-to-ship missile systems, 60 anti-tank missile launchers, 12 light fighter jets, and a total force of 6,000 personnel.

[0085] Step 2, construct the inference model:

[0086] Establish a full-process simulation framework covering "pre-battle preparation - troop deployment - beachhead assault - in-depth advance - combat cleanup", and clarify the simulation logic and judgment criteria for each stage:

[0087] Pre-battle preparation phase: Simulates the attacking side's reconnaissance, material gathering, and tactical deployment, and the defending side's reinforcement of defensive fortifications and adjustment of troop deployment. The criteria for judgment are that the attacking side completes reconnaissance and troop gathering, and the defending side completes defensive deployment.

[0088] Troop deployment phase: Simulates the troop deployment process of the attacking side's amphibious ships, hovercraft, and helicopters. The judgment criterion is the successful arrival of the first batch of landing troops (2,000 people) on the beachhead.

[0089] Beachhead assault phase: Simulates the attacking side breaking through the beach defenses and the defending side launching a counterattack. The criterion for judgment is that the attacking side breaks through the enemy's first line of defense on the beach and controls the beach landing area (with an area of ​​no less than 2 square kilometers).

[0090] In-depth advance phase: The attacking force advances towards the central hills, airport, and port of the island, while the defending force implements ambushes and in-depth defense. The criteria for judgment are that the attacking force controls the airport and port and annihilates the core defensive forces of the defending force.

[0091] The final stage of the operation: The attacking side simulates clearing out the remaining enemy forces and consolidating their positions, while the remaining defenders break out or surrender. The operation ends when the attacking side has completely controlled the target island.

[0092] Step 3: Input the hypothetical parameters and conduct phased deductions:

[0093] Enter the above-mentioned assumed parameters into the simulation model, start the simulation system, and conduct simulations in stages:

[0094] Pre-battle preparation phase (simulation time: 24 hours): The attacking special forces infiltrate the target island, complete the reconnaissance of the terrain and the deployment of the defending forces, and transmit real-time intelligence; the attacking amphibious combat formation assembles on our coast, completes the resupply of materials and tactical coordination training; the defending side reinforces the beach defense fortifications, adjusts the deployment of forces, activates radar and drone reconnaissance, and makes preparations for defense.

[0095] Troop deployment phase (simulation time: 8 hours): The attacking amphibious assault formation departs from our coast and sails towards the target island. En route, it encounters reconnaissance drones from the defending side. Attacking fighter jets scramble to intercept and shoot down 3 defending drones. After arriving at the nearshore waters of the target island, hovercraft carrying amphibious tanks and infantry fighting vehicles deploy troops to the eastern beach. The defending side launches coastal defense artillery and shore-to-ship missiles to intercept them. The attacking side's missile frigates launch anti-aircraft missiles to intercept the defending side's shore-to-ship missiles. The amphibious assault ship launches helicopters to provide air support. Ultimately, the attacking side's first batch of 2,000 troops successfully reaches the beachhead, losing 2 hovercraft and 3 amphibious infantry fighting vehicles, with 120 casualties. The defending side loses 4 coastal defense artillery pieces and 1 shore-to-ship missile system, with 80 casualties.

[0096] Beachhead assault phase (simulation time: 12 hours): The attacking force launches its assault, using amphibious tanks to break through enemy barbed wire and anti-tank ditches. Long-range rocket artillery and air attack aircraft bombard the defending force's beach defenses, destroying 12 bunkers and 3 minefields. The defending force, relying on its fortifications, retaliates with anti-tank missiles and anti-aircraft guns, shooting down 4 attacking helicopters and destroying 5 attacking amphibious tanks. Ultimately, the attacking force breaks through the first line of defense on the defending beach, controlling a 3-square-kilometer landing zone. The attacking force suffers 350 casualties and loses 5 amphibious tanks and 8 infantry fighting vehicles. The defending force suffers 600 casualties and loses 8 anti-tank missile launchers and 12 coastal defense guns.

[0097] In-depth advance phase (simulation time: 24 hours): Subsequent attacking forces land successively and advance towards the central hills, airport, and port of the island. They encounter ambushes from the defenders in the hilly area. The attacking mechanized forces engage in fierce battles with the defenders' tanks and anti-tank units, with close air support provided by fighter jets and attack aircraft. They destroy 15 main battle tanks and 6 air defense missile systems of the defenders. The attacking special forces infiltrate the defenders' airport, destroy the airport runway and command facilities, and assist the main force in capturing the airport. Ultimately, the attacking forces control the airport and port, annihilating 3,000 core defenders. The attacking forces suffer 580 casualties and lose 3 fighter jets, 6 helicopters, and 8 amphibious tanks. The defenders suffer 3,000 casualties and lose 8 light fighter jets, 15 main battle tanks, and 10 shore-to-ship missile systems.

[0098] Final stage of the operation (simulation time: 12 hours): The attacking side clears out the remaining enemy forces on the island, consolidates its position, treats the wounded, and replenishes supplies; the remaining 1,000 defenders surrender after failing to break out; finally, the attacking side completely controls the target island, and the operation ends, with a total simulation time of 72 hours.

[0099] Step 4, Analysis and Optimization of Deduction Results:

[0100] Collect various data during the simulation process and analyze the strengths and weaknesses of the combat plan:

[0101] Advantages: The attacking force has a high efficiency in deploying troops, and its air support and fire suppression are effective, successfully breaking through the defending force's beach defenses and controlling key targets;

[0102] Shortcomings: The beachhead assault phase resulted in significant losses of personnel and equipment, mainly due to insufficient reconnaissance of the defenders' anti-tank missile deployment locations, slow progress in hilly terrain, and the need to improve logistical support efficiency.

[0103] To address the aforementioned shortcomings, the operational plan was optimized as follows: First, pre-battle reconnaissance efforts were increased, with more drones deployed to accurately locate the positions of the defenders' anti-tank missiles and fortifications; second, troop deployment was adjusted, with more armed helicopters deployed in hilly areas to support the advance of mechanized forces; and third, logistical supply routes were optimized, utilizing hovercraft and helicopters to rapidly replenish supplies and improve supply efficiency.

[0104] Step 5, Deduction, Verification, and Iteration:

[0105] Following the optimized operational plan, repeat the above simulation steps to conduct a second round of simulations and verify the feasibility of the plan:

[0106] In the second round of simulations, the attacking side, through precise reconnaissance, destroyed 12 anti-tank missile launchers of the defending side in advance. During the beachhead assault phase, casualties were reduced to 220, and equipment losses were reduced to 3 amphibious tanks and 5 infantry fighting vehicles. The advance speed in hilly areas increased by 30%, and the efficiency of logistical support increased by 25%. In the end, the attacking side completely controlled the target island, with total casualties reduced to 950 and equipment losses significantly reduced. The simulation results showed that the optimized combat plan was more feasible and reasonable.

[0107] Through repeated rounds of simulations and continuous optimization of the operational plan, an optimal island attack operation simulation report was finally generated, providing a reference for actual combat command and decision-making.

[0108] Compared with the prior art, the present invention has the following beneficial effects:

[0109] Highly targeted: Specifically designed for the characteristics of amphibious joint operations in island assault operations, it sets specific and quantifiable assumptions about personnel, weapons, equipment, terrain, and climate on both sides, closely matching actual combat scenarios and solving the problems of general assumptions and insufficient targeting in existing simulation methods;

[0110] High accuracy: A multi-factor collaborative simulation model has been constructed, realizing the dynamic linkage of multiple factors such as terrain, climate, weapon performance, and personnel deployment. It can accurately simulate the entire process of island attack operations, and the simulation results are more realistic and have more reference value.

[0111] Highly practical: Through phased simulations, results analysis and optimization, and multiple rounds of verification, the feasibility of island attack operation plans can be quickly verified, troop deployment, weapon use and tactical coordination can be optimized, and reliable support can be provided for combat command decisions and tactical training.

[0112] Highly scalable: The assumptions and simulation parameters can be adjusted according to the actual combat scenario. The simulation model can be flexibly adapted to the simulation needs of island attack operations under different scales, terrains, and climates, and has a wide range of applications.

[0113] Although the present invention has been described in detail above, it is not limited thereto, and those skilled in the art can make various modifications based on the principles of the present invention. Therefore, all modifications made in accordance with the principles of the present invention should be understood to fall within the protection scope of the present invention.

Claims

1. A wargaming method based on intelligent agents, used for island warfare simulations, characterized in that, Includes the following steps: Intelligent agents are used to set inference parameters, including terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters of the combat area; Construct a deductive model that includes a parameter correlation mapping system, a dynamic calculation engine, and a feedback iteration mechanism; The inference parameters are input into the inference model, and the inference is carried out in stages to obtain the inference results; The simulation results are analyzed and optimized by collecting various data during the simulation process, analyzing the advantages and disadvantages of the combat plan, and optimizing the plans for troop deployment, weapon use, and tactical coordination. The simulation and iteration process involves repeating the above simulation steps and conducting multiple rounds of simulations to verify the feasibility and stability of the optimized plan, ultimately forming the final island attack operation simulation report.

2. The agent-based wargaming method according to claim 1, characterized in that, The phased simulation includes: conducting phased simulations based on the operational process of pre-war preparation, troop deployment, beachhead assault, in-depth advance, and combat conclusion; calculating operational losses, advance efficiency, and objective achievement in each phase in real time; and dynamically adjusting simulation parameters.

3. The agent-based wargaming method according to claim 1, characterized in that, Create a parameter association mapping system in the following way: Establish quantitative sub-parameters for terrain parameters, climate parameters, personnel deployment parameters, and weapon performance parameters; Determine the rules governing the influence between quantized sub-parameters; Determine the derived parameters related to the quantized sub-parameters based on the influence rules among the quantized sub-parameters; Establish a mapping relationship between one or more quantization sub-parameters and their corresponding derived parameters.

4. The agent-based wargaming method according to claim 3, characterized in that, The quantifiable sub-parameters of terrain parameters include shore slope, water depth, and vegetation coverage; the quantifiable sub-parameters of climate parameters include wind speed, wave height, and visibility; and the quantifiable sub-parameters of weapon performance parameters include amphibious tank water speed and fire accuracy.

5. The agent-based wargaming method according to claim 4, characterized in that, The rules governing the influence between quantifiable sub-parameters include: Wave height correlates with a decrease in the speed of the air-cushioned landing craft. High vegetation coverage reduces the speed of personnel advancement and increases the success rate of ambushes by the defending side.

6. The agent-based wargaming method according to claim 5, characterized in that, By establishing a mapping relationship between quantifiable sub-parameters including beach slope and wind speed, quantifiable parameters of fire strike accuracy, and derived parameters including landing efficiency and fire strike accuracy, derived parameters including landing efficiency and fire strike accuracy are obtained; the derived parameters are then used to extrapolate the calculation results of each simulation stage, including troop deployment and beachhead assault.

7. The agent-based wargaming method according to claim 6, characterized in that, The dynamic computing engine performs the following operations: Input various quantifiable sub-parameters into the calculation engine and assign each sub-parameter a unique identifier and quantization weight; When a certain sub-parameter changes, the computing engine automatically triggers a correlation retrieval to extract all correlation rules corresponding to that parameter; Based on the quantized weights, the calculation functions of the relevant deduction steps are dynamically adjusted; Synchronously update the derived values ​​of associated parameters.

8. The agent-based wargaming method according to claim 6, characterized in that, The feedback iteration mechanism includes: During the simulation, after each type of parameter changes, the engine immediately outputs the adjusted simulation data and synchronously feeds it back to all related simulation stages.

9. The agent-based wargaming method according to claim 8, characterized in that, The feedback iteration mechanism includes: By combining data from multiple rounds of simulations, the system automatically optimizes the weights associated with parameters, ensuring that parameter linkages better align with real-world logic.

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