Policy decision support device, policy decision support method, and policy decision support program

Abstract

This invention provides a policy decision support device, a policy decision support method, and a policy decision support program that can identify important factors when deciding on policies. [Solution] The system includes a derivation unit that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and an identification unit that identifies factors that satisfy the commonality criterion among multiple different preconditions from which the derivation unit has derived a policy implementation plan that satisfies the same or similar criteria as common factors within the group.

Description

Technical Field

[0001] The present disclosure relates to a policy decision support device, a policy decision support method, and a policy decision support program.

Background Art

[0002] As a technology related to policy decision support, for example, Patent Document 1 discloses a technology for supporting the decision of corporate policies regarding products.

[0003] In the corporate policy decision support device described in Patent Document 1, the prediction share calculation means calculates a future predicted share for the input analysis target segment using the transition probability matrix and the current share. The optimal corporate policy decision means determines an optimal corporate policy that maximizes the value obtained by subtracting the cost required for the execution of the corporate policy from the sales amount of the company's own products based on the future predicted share of the company's own products.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The prediction of the future transition of policy parameters that affect policy decisions depends on preconditions. Therefore, an infinite number of prediction results of the future transition of policy parameters are generated according to the preconditions. Although important and unimportant preconditions are mixed, the technology described in Patent Document 1 cannot distinguish between them. As a result, the user has to spend time examining the preconditions.

[0006] This disclosure is made in light of these issues. One of the purposes of this disclosure is to provide a policy decision support device, a policy decision support method, and a policy decision support program that can identify important factors when deciding on policies. [Means for solving the problem]

[0007] The policy decision support device disclosed herein includes a derivation unit that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and an identification unit that identifies factors that satisfy the criteria for commonality among multiple preconditions that satisfy the criteria for commonality among multiple preconditions from which a policy implementation plan satisfying the same or similar criteria has been derived by the derivation unit, as common factors within the group.

[0008] The policy decision support method disclosed herein involves a computer deriving a policy implementation plan based on the projected future trends of policy parameters by applying preconditions, and identifying factors that satisfy the commonality criterion among multiple different preconditions that satisfy the same or similar criteria as common factors within the group.

[0009] The policy decision support program disclosed herein causes a computer to perform a derivation process that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and an identification process that identifies factors that satisfy the commonality criterion among multiple different preconditions from which a policy implementation plan satisfying the same or similar criteria has been derived in the derivation process, as common factors within the group. [Effects of the Invention]

[0010] This disclosure allows for the identification of important factors when deciding on policies. [Brief explanation of the drawing]

[0011] [Figure 1] This is a block diagram illustrating the functional configuration of a policy decision support device. [Figure 2]This is an explanatory diagram illustrating the general operation of a policy decision support device. [Figure 3] This is a flowchart illustrating the operation of a policy decision support system. [Figure 4] This is a block diagram illustrating the functional configuration of a policy decision support device. [Figure 5] This is a flowchart illustrating the operation of a policy decision support system. [Figure 6] This is a block diagram illustrating the hardware configuration of a computer that implements a policy decision support system. [Figure 7] This is a block diagram illustrating the main components of a policy decision support system. [Figure 8] This is a block diagram illustrating the main components of other policy decision support devices. [Modes for carrying out the invention]

[0012] An increasing number of companies are setting decarbonization targets and engaging in decarbonization management through measures such as disclosing management strategies that address climate change (TCFD (Task Force on Climate-related Financial Disclosures)) and setting targets for decarbonization (SBT (Science Based Targets)).

[0013] To achieve decarbonization targets, it is necessary to formulate cost-effective decarbonization implementation plans that take into account future developments in energy-related technologies (such as the efficiency of solar power generation) and fluctuations in energy prices.

[0014] Related general technologies include technologies that predict future trends in policy parameters that influence policy decisions (e.g., energy unit prices, fuel unit prices, renewable energy generation efficiency, etc.) and technologies that present the basis for predictions (i.e., the assumptions).

[0015] For example, the following Document 1 discloses a technique that utilizes an LLM (Large Language Models) that combines time-series data and text data to predict time-series data. Further, the following Document 2 discloses an XAI (Explainable AI) technique that explains why AI (Artificial Intelligence) made such a judgment so that humans can understand it. Document 1: "Large Language Model for Time-Series Data", [online], [searched on September 17, 2024], Internet, <URL:https: / / zenn.dev / tsurubee / articles / 00446669b6c83a> Document 2: "What is XAI (Explainable AI)? - Explanation of meaning, methods, merits, introduction issues, use cases, etc.", [online], [searched on September 17, 2024], Internet, <URL:https: / / qiita.com / skillup_ai / items / ec498402829a5843dfeb>

[0016] The prediction of the future trend of policy parameters that affect policy decisions depends on preconditions. Therefore, an infinite number of prediction results of the future trend of policy parameters are generated according to the preconditions. Furthermore, although important and unimportant preconditions are mixed, general technologies cannot distinguish between them. As a result, users such as business operators will spend time examining the preconditions. In addition, users such as business operators cannot easily determine which prediction results and policy implementation plans should be adopted.

[0017] In the technology related to the present disclosure, the policy decision support device derives a policy implementation plan from the future transition of policy parameters, and identifies prerequisite conditions (common factors) common to "future transitions that result in policy execution plans that meet the same or similar criteria". Further, the policy decision support device identifies prerequisite conditions (differential factors) that result in different policy implementation plans based on the above common factors. As a result, users such as business operators can recognize important factors when determining a policy implementation plan. In addition, users such as business operators can suitably adopt prediction results and policy implementation plans in which important factors are reflected.

[0018] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and redundant descriptions are omitted as necessary for clarity of explanation. Unless otherwise specified, predetermined values such as predetermined values and threshold values are stored in advance in a storage device or the like accessible from the device that uses the values. Further, unless otherwise specified, the storage unit is composed of one or more arbitrary storage devices.

[0019] Embodiment 1. The functional configuration of the policy decision support device according to this embodiment will be described. FIG. 1 is a block diagram illustrating the functional configuration of the policy decision support device. The policy decision support device 100 according to this embodiment includes a prediction unit 110, a derivation unit 120, a classification unit 130, a specification unit 140, a collection unit 150, and an output unit 160.

[0020] The prediction unit 110 has a function of predicting the future transition of policy parameters by applying prerequisite conditions. Hereinafter, the "future transition of policy parameters" will also be simply referred to as "future transition".

[0021] The policy is, for example, a policy aimed at decarbonization, but is not limited thereto. Specific examples of policies include the introduction of solar power generation facilities, the conclusion of power purchase agreements (Power Purchase Agreement), the construction of virtual power plants (Virtual Power Plant), the introduction of energy-saving equipment, the purchase of carbon credits, the electrification of equipment, and the procurement of CO2-free electricity.

[0022] Policy parameters are parameters that influence policy decisions. Specific examples of policy parameters include energy unit prices, fuel unit prices, and renewable energy generation efficiency.

[0023] Assumptions are the conditions that serve as the basis for predicting the future trends of policy parameters. Assumptions may include multiple factors. Specific examples of factors included in assumptions include, for example, international affairs, policy trends, and technological trends.

[0024] The derivation unit 120 has the function of deriving a policy implementation plan based on the future trends of policy parameters predicted by applying the given assumptions.

[0025] The derivation unit 120 derives a policy implementation plan according to predetermined criteria, for example, based on the future trends of policy parameters. The derivation unit 120 can apply various criteria as predetermined criteria. For example, consider a case where the policy implementation plan is in a format that indicates which areas, when, and what kind of policies to implement. In this case, the derivation unit 120 derives the optimal combination of which areas, when, and what kind of policies to implement. The derivation unit 120 can use various optimization methods, such as greedy algorithms, local search methods, simulated annealing, and genetic algorithms. However, the optimization methods applicable to the derivation unit 120 are not limited to these methods.

[0026] The classification unit 130 has the function of associating derived policy implementation plans with the assumptions applied when deriving said policy implementation plans. The classification unit 130 also has the function of classifying assumptions associated with policy implementation plans that meet the same or similar criteria into the same group.

[0027] The classification unit 130 can determine whether a policy implementation plan meets similar criteria to other policy implementation plans by applying the methods shown below. However, the determination methods applicable to the classification unit 130 are not limited to those shown below.

[0028] For example, the classification unit 130 determines that the first and second policy implementation plans meet the criteria for similarity if their similarity exceeds a predetermined threshold. Alternatively, the classification unit 130 may determine that the first and second policy implementation plans meet the criteria for similarity if, among multiple policy implementation plans, the second policy implementation plan has the highest similarity to the first policy implementation plan. Furthermore, the classification unit 130 can determine similarity in various ways. For example, the classification unit 130 may determine that the first and second policy implementation plans have a high degree of similarity if they both contain similar measures. Additionally, the classification unit 130 may determine that the similarity is high if the timing and area of ​​implementation of similar measures are close together. Finally, the classification unit 130 may also determine that the similarity is high if the implementation of similar measures is similar to those of the first and second policy implementation plans. Similar measures are, for example, a measure to purchase renewable energy-derived electricity from company A and a measure to purchase renewable energy-derived electricity from company B. Even if the effects and costs are not exactly the same, they are essentially the same measures.

[0029] The identification unit 140 has the function of identifying factors that satisfy the commonality criterion among multiple preconditions that satisfy the same or similar criteria, for which the derivation unit 120 has derived a policy implementation plan that satisfies the same or similar criteria, as common factors within the group. For example, the identification unit 140 identifies factors that satisfy the commonality criterion among multiple preconditions that have been classified into the same group by the classification unit 130, as common factors within the group.

[0030] The identification unit 140 can determine whether the factors meet the commonality criteria by applying various methods, as shown below. However, the determination methods that the identification unit 140 can apply are not limited to those shown below.

[0031] For example, the identification unit 140 determines that a factor satisfies the commonality criterion if the same factor is included in both the first and second preconditions classified into the same group. The identification unit 140 may also determine that the first and second factors satisfy the commonality criterion if the similarity between the first factor included in the first precondition and the second factor included in the second precondition exceeds a predetermined threshold. In this case, the identification unit 140 may use as a premise for its determination that the first factor is not included in the second precondition and the second factor is not included in the first precondition.

[0032] Furthermore, the identification unit 140 may determine that factors that are included in a predetermined percentage (for example, 90%) or more of the preconditions within a group satisfy the commonality criterion, rather than limiting itself to factors included in all preconditions within the group. Specifically, if n preconditions are classified into the same group, the identification unit 140 may determine that factors that are included in a predetermined percentage or more of the n preconditions satisfy the commonality criterion.

[0033] The identification unit 140 has the function of identifying factors that differ between a group-wide common factor corresponding to one policy implementation plan and a group-wide common factor corresponding to a policy implementation plan different from that one policy implementation plan, as inter-group difference factors.

[0034] A "policy implementation plan different from one policy implementation plan" refers to another policy implementation plan that is not determined to meet the same or similar criteria as one policy implementation plan. As described above, the classification unit 130 can determine whether a policy implementation plan meets the same or similar criteria as other policy implementation plans by applying various methods.

[0035] If the number of preconditions is insufficient or if there is a bias in the preconditions, the identification unit 140 may not be able to identify common factors within a group that satisfy the commonality criteria. In such cases, the identification unit 140 may identify all factors of all preconditions belonging to the same group as common factors within the group. Alternatively, the identification unit 140 may identify the differences between the commonly identified common factors within a group and common factors within other groups as intergroup difference factors. Furthermore, the identification unit 140 may always identify all factors of all preconditions belonging to the same group as common factors within the group, not only when it is unable to identify common factors within a group that satisfy the commonality criteria.

[0036] The collection unit 150 has the function of collecting and outputting information related to the factors identified by the identification unit 140. For example, the collection unit 150 collects information related to common factors within a group and differentiating factors between groups from sources such as Web (World Wide Web) news, SNS (Social Networking Service) information, and academic paper data. The collection unit 150 may collect information related to the identified factors from outside the policy decision support device 100, or it may collect it from a storage unit within the policy decision support device 100 (for example, a storage unit that stores such information that has been collected in advance). The collection unit 150 outputs the collected information via the output unit 160.

[0037] The output unit 160 has a function to output information indicating the factors identified by the identification unit 140. The output unit 160 may output information related to the factors collected by the collection unit 150 as information indicating the identified factors.

[0038] The output unit 160 outputs and stores information indicating the identified factors to the policy decision support device 100 or the storage unit (not shown) of an external device. The output unit 160 also outputs and displays information indicating the identified factors to a display device (not shown), such as a display device.

[0039] The output unit 160 may output information indicating the identified factors, along with information indicating policy implementation plans and assumptions classified into the same group by the classification unit 130. The output unit 160 may also output information indicating the future trends of policy parameters predicted by the forecasting unit 110 by applying the assumptions.

[0040] Next, the operation overview of the policy decision support device 100 will be explained. Figure 2 is an explanatory diagram illustrating the operation overview of the policy decision support device 100. Note that the explanatory diagram shown in Figure 2 does not limit the operation of the policy decision support device 100.

[0041] Figure 2 shows the cases where each of the four preconditions—Precondition 1, Precondition 2, Precondition 3, and Precondition 4—is applied.

[0042] Prerequisite 1 includes three factors: "International situation: Pattern A", "Policy trends: Pattern A", and "Technological trends: Pattern A". Prerequisite 2 includes three factors: "International situation: Pattern A", "Policy trends: Pattern B", and "Technological trends: Pattern A". Prerequisite 3 includes three factors: "International situation: Pattern B", "Policy trends: Pattern B", and "Technological trends: Pattern A". Prerequisite 4 includes three factors: "International situation: Pattern B", "Policy trends: Pattern A", and "Technological trends: Pattern A".

[0043] In the example shown in Figure 2, the factors included in the preconditions consist of items such as international affairs, policy trends, and technological trends, as well as evaluations corresponding to these items, such as Pattern A and Pattern B. However, the format of the factors included in the preconditions is not limited to this. Furthermore, the preconditions are not limited to the example shown in Figure 2; they may include one or two factors, or four or more factors.

[0044] The prerequisite factors are generated, for example, by a computer combining items and evaluations according to predetermined criteria. Furthermore, some or all of the prerequisite factors may be generated according to user input.

[0045] In the example shown in Figure 2, the prediction unit 110 applies condition 1 to predict the future trend of the policy parameters as prediction 1. The prediction unit 110 also applies condition 2 to predict the future trend of the policy parameters as prediction 2. The prediction unit 110 also applies condition 3 to predict the future trend of the policy parameters as prediction 3. The prediction unit 110 also applies condition 4 to predict the future trend of the policy parameters as prediction 4.

[0046] In the example shown in Figure 2, the derivation unit 120 derives policy implementation plan A based on prediction 1. The derivation unit 120 also derives policy implementation plan A based on prediction 2. Furthermore, the derivation unit 120 derives policy implementation plan B based on prediction 3. Finally, the derivation unit 120 derives policy implementation plan B based on prediction 4.

[0047] In the example shown in Figure 2, the classification unit 130 groups preconditions 1 and 2 that lead to the same policy implementation plan A as group A. The classification unit 130 also groups preconditions 3 and 4 that lead to the same policy implementation plan B as group B.

[0048] In the example shown in Figure 2, the identification unit 140 identifies two factors, "International situation: Pattern A" and "Technological trends: Pattern A," as common intragroup factors that satisfy the commonality criterion between precondition 1 and precondition 2, which are classified as Group A. Furthermore, the identification unit 140 identifies two factors, "International situation: Pattern B" and "Technological trends: Pattern A," as common intragroup factors that satisfy the commonality criterion between precondition 3 and precondition 4, which are classified as Group B.

[0049] Furthermore, the specific section 140 identifies "international situation" as an intergroup difference factor that causes a difference between the common factors within the group corresponding to policy implementation plan A (i.e., group A) and the common factors within the group corresponding to policy implementation plan B (i.e., group B).

[0050] As shown in Figure 2, the policy decision support device 100 identifies the common factors within policy implementation plan A (i.e., group A), namely "International situation: A pattern" and "Technological trends: A pattern." This allows the user to recognize important factors when considering whether to adopt policy implementation plan A. In other words, when considering policy implementation plan A, the user does not need to scrutinize all the factors of precondition 1 and precondition 2, but can make a suitable decision based solely on the common factors within the group. For example, the user can determine whether to adopt policy implementation plan A by checking for any inconsistencies in the common factor "Technological trends: A pattern." As a result, the user can suitably adopt prediction results and policy implementation plans that reflect important factors. In this way, the policy decision support device 100 can minimize the amount of information used to make decisions when considering the adoption of a policy implementation plan.

[0051] Furthermore, as shown in Figure 2, the policy decision support device 100 identifies the intergroup difference factor "international situation." This allows the user to recognize important factors when deciding whether to adopt the derived policy implementation plan A or policy implementation plan B. For example, if the user determines that "international situation: pattern A" is more appropriate than "international situation: pattern B," they will decide to adopt policy implementation plan A from group A. As a result, the user can suitably adopt the prediction results and policy implementation plans that reflect the important factors. In this way, the policy decision support device 100 can further minimize the number of factors used in considering the adoption of a policy implementation plan.

[0052] Next, the operation of the policy decision support device 100 will be explained. Figure 3 is a flowchart illustrating the operation of the policy decision support device 100.

[0053] The prediction unit 110 predicts the future trends of policy parameters by applying preconditions (step S101). For example, the prediction unit 110 predicts the future trends of policy parameters for each of several different preconditions.

[0054] Next, the derivation unit 120 derives a policy implementation plan based on the predicted future trends of the policy parameters (step S102). For example, the derivation unit 120 derives a policy implementation plan for each predicted future trend of the policy parameters.

[0055] Next, the classification unit 130 associates the derived policy implementation plan with the assumptions applied when deriving the policy implementation plan. Then, the classification unit 130 classifies the assumptions associated with policy implementation plans that satisfy the same or similar criteria into the same group (step S103).

[0056] Next, the identification unit 140 identifies factors that satisfy the commonality criteria among multiple preconditions classified into the same group as common factors within the group (step S104).

[0057] Next, the identification unit 140 identifies factors that differ between the common factors within one group and the common factors within another group as intergroup difference factors (step S105).

[0058] Next, the collection unit 150 collects information related to the factors identified by the identification unit 140 (step S106).

[0059] Next, the output unit 160 outputs information indicating the factors identified by the identification unit 140 and information related to the factors collected by the collection unit 150 (step S107).

[0060] Note that the example of operation shown in Figure 3 does not limit the operation of the policy decision support device 100 of this disclosure. For example, if the classification unit 130 classifies all preconditions into a single group, the identification unit 140 may omit the processing in step S105.

[0061] Furthermore, after the processing in step S107 shown in Figure 3, the policy decision support device 100 may receive condition information indicating the conditions for generating the policy implementation plan based on user input. In this case, the generation unit of the policy decision support device 100 (not shown in Figure 1; may be implemented by the derivation unit 120) can generate a policy implementation plan based on common factors within the group and differentiating factors between groups that satisfy the conditions. The output unit 160 can also output information indicating the policy implementation plan generated by the generation unit.

[0062] For example, if the policy decision support device 100 outputs information indicating that it has identified "international situation" as a group difference factor, the user decides whether to adopt "international situation: pattern A" or "international situation: pattern B". The user then performs an operation to input condition information that specifies the adopted option. The generation unit of the policy decision support device 100 then generates a policy implementation plan based on the input condition information. For example, if the generation unit of the policy decision support device 100 receives condition information indicating that "international situation: pattern A" will be adopted, it will generate a policy implementation plan based on the future trends of policy parameters, including "international situation: pattern A" as a prerequisite.

[0063] For example, if the policy decision support device 100 outputs information indicating that it has identified "International Situation: Pattern A" and "Technological Trends: Pattern A" as common factors within the group, the user will determine whether the common factors within the group are appropriate. If the user determines that they are appropriate, the user will then input conditional information that includes "International Situation: Pattern A" and "Technological Trends: Pattern A" as conditions. The generation unit of the policy decision support device 100 will then generate a policy implementation plan based on the future trends of policy parameters that include "International Situation: Pattern A" and "Technological Trends: Pattern A" as preconditions.

[0064] If new "future trends of policy parameters" are obtained during the consideration of the policy implementation plan or after the start of operation of the policy implementation plan, the policy decision support device 100 may operate as follows.

[0065] In other words, the derivation unit 120 derives a policy implementation plan based on the future trends of the new policy parameters. Next, if the newly derived policy implementation plan satisfies the same or similar criteria as an existing policy implementation plan, the classification unit 130 classifies the newly derived policy implementation plan into the group corresponding to the existing policy implementation plan. Next, the identification unit 140 identifies common factors within that group. After that, the policy decision support device 100 executes the processes in steps S106 to S107.

[0066] On the other hand, if the newly derived policy implementation plan differs from an existing policy implementation plan, the classification unit 130 generates a new group corresponding to the newly derived policy implementation plan. Next, the identification unit 140 identifies the intergroup difference factors between the newly generated group and the existing group. After that, the policy decision support device 100 executes the processes in steps S106 to S107.

[0067] Next, the effects of this embodiment will be described. In this embodiment, the derivation unit 120 derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions. The identification unit 140 identifies factors that satisfy the commonality criterion among multiple preconditions that satisfy the same or similar criteria as group common factors for multiple preconditions from which a policy implementation plan satisfying the same or similar criteria has been derived by the derivation unit 120. With this configuration, the policy decision support device 100 can identify group common factors that satisfy the commonality criterion among multiple preconditions. As a result, the user can recognize factors that are important for decision-making when considering whether to decide on the derived policy implementation plan. In other words, when the user considers the policy implementation plan, it is not necessary to scrutinize all the factors of the preconditions, and a suitable decision can be made based only on the group common factors. Furthermore, the user can suitably adopt the prediction results and policy implementation plan that reflect the important factors. In this way, the policy decision support device 100 can minimize the amount of decision-making material used when considering the adoption of a policy implementation plan.

[0068] Furthermore, the identification unit 140 identifies factors that differ between a group-wide common factor corresponding to one policy implementation plan and a group-wide common factor corresponding to a policy implementation plan different from that one, as inter-group difference factors. With this configuration, the policy decision support device 100 can identify inter-group difference factors that differ between groups. As a result, the user can recognize factors that are important for making a decision when deciding which of the derived policy implementation plans to adopt. In addition, the user can suitably adopt prediction results or policy implementation plans that reflect these important factors. In this way, the policy decision support device 100 can further minimize the amount of information used for decision-making when considering the adoption of a policy implementation plan.

[0069] In this embodiment, the collection unit 150 collects information related to the factors identified by the identification unit 140. The output unit 160 outputs information indicating the factors identified by the identification unit 140 and information related to the factors collected by the collection unit 150. With this configuration, the user can obtain important factors and related information when considering a policy implementation plan.

[0070] Embodiment 2. The functional configuration of the policy decision support device of this embodiment will now be described. Below, we will omit descriptions of parts that are the same as those of the first embodiment, and mainly describe the parts that differ from the first embodiment.

[0071] Figure 4 is a block diagram illustrating the functional configuration of the policy decision support device. The policy decision support device 200 includes a prediction unit 110, a classification unit 230, a specific unit 240, a collection unit 150, and an output unit 160.

[0072] The prediction unit 110, data collection unit 150, and output unit 160 of the policy decision support device 200 shown in Figure 4 have the same functional configuration as the prediction unit 110, data collection unit 150, and output unit 160 of the policy decision support device 100 shown in Figure 1. Note that the prediction unit 110 may be implemented by a different device than the policy decision support device 200.

[0073] The policy decision support device 200 shown in Figure 4 does not have a functional configuration equivalent to the output unit 120 of the policy decision support device 100 shown in Figure 1. Furthermore, the policy decision support device 200 shown in Figure 4 includes a classification unit 230 and a specification unit 240 instead of the classification unit 130 and specification unit 140 of the policy decision support device 100 shown in Figure 1.

[0074] The classification unit 230 has the function of associating the future trends of policy parameters predicted by the forecasting unit 110 with the assumptions applied when predicting those future trends. The classification unit 230 also has the function of classifying assumptions associated with future trends that meet the same or similar criteria into the same group.

[0075] The classification unit 230 can determine whether a predicted future trend meets similar criteria to other predicted future trends by applying the methods shown below. However, the determination methods applicable to the classification unit 230 are not limited to those shown below.

[0076] For example, the classification unit 230 determines that the first future trend and the second future trend meet the criteria for similarity if their similarity exceeds a predetermined threshold. Alternatively, the classification unit 130 may determine that the first and second future trends meet the criteria for similarity if the second future trend is the one with the highest similarity among several future trends. Furthermore, the classification unit 230 can determine similarity in various ways. For example, the classification unit 230 may determine that the similarity is high if both the value of the first future trend and the value of the second future trend are showing an increasing or decreasing trend. The classification unit 230 may also determine that the similarity is high if singularities appear in both the first and second future trends. Moreover, the classification unit 230 may determine that the closer the timing of the singularities, the higher the similarity.

[0077] The identification unit 240 has the function of identifying factors that satisfy the commonality criterion among multiple different assumptions whose future trends are predicted by the prediction unit 110 to satisfy the same or similar criteria, as common factors within the group. For example, the identification unit 240 identifies factors that satisfy the commonality criterion among multiple assumptions that have been classified into the same group by the classification unit 230 as common factors within the group.

[0078] The identification unit 240 has the function of identifying factors that result in differences between a common group factor corresponding to one future trend and a common group factor corresponding to a future trend different from that one future trend, as intergroup difference factors.

[0079] "A future trend different from one future trend" refers to another predicted future trend that is not determined to meet the same or similar criteria as one predicted future trend. As described above, the classification unit 230 can apply various methods to determine whether a predicted future trend meets the same or similar criteria as other predicted future trends.

[0080] Next, the operation of the policy decision support device 200 will be explained. Figure 5 is a flowchart illustrating the operation of the policy decision support device 200.

[0081] The prediction unit 110 predicts the future trends of policy parameters by applying preconditions (step S201). For example, the prediction unit 110 predicts the future trends of policy parameters for each of several different preconditions.

[0082] Next, the classification unit 230 associates the projected future trends of the policy parameters with the assumptions applied when projecting those future trends. Then, the classification unit 230 classifies the assumptions associated with future trends that satisfy the same or similar criteria into the same group (step S202).

[0083] Next, the identification unit 240 identifies factors that satisfy the commonality criteria among multiple preconditions classified into the same group as common factors within the group (step S203).

[0084] Next, the identification unit 240 identifies factors that differ between the common factors within one group and the common factors within another group as intergroup difference factors (step S204).

[0085] Next, the collection unit 150 collects information related to the factors identified by the identification unit 240 (step S205).

[0086] Next, the output unit 160 outputs information indicating the factors identified by the identification unit 240 and information related to the factors collected by the collection unit 150 (step S206).

[0087] Note that the example of operation shown in Figure 5 does not limit the operation of the policy decision support device 200. For example, if the classification unit 230 classifies all preconditions into a single group, the identification unit 240 may omit the processing in step S204.

[0088] Furthermore, as described in relation to the flowchart shown in Figure 3, the policy decision support device 200 may, after processing in step S206 shown in Figure 5, input condition information indicating the conditions for generating the policy implementation plan based on user input. In this case, the generation unit of the policy decision support device 200 (not shown in Figure 4; may be implemented by the derivation unit 120 shown in Figure 1) can generate a policy implementation plan based on common factors within the group and differentiating factors between groups that satisfy the conditions. The output unit 160 can also output information indicating the policy implementation plan generated by the generation unit.

[0089] If new "future trends of policy parameters" are obtained during the consideration of the policy implementation plan or after the start of operation of the policy implementation plan, the policy decision support device 200 may operate as follows.

[0090] In other words, if the future trends of a new policy parameter meet the same or similar criteria as the future trends of an existing policy parameter, the classification unit 230 classifies the future trends of the new policy parameter into a group corresponding to the future trends of the existing policy parameter. Next, the identification unit 240 identifies common factors within that group. After that, the policy decision support device 200 executes the processes in steps S205 to S206.

[0091] On the other hand, if the future trends of the new policy parameters differ from those of the existing policy parameters, the classification unit 230 generates a new group corresponding to the future trends of the new policy parameters. Next, the identification unit 240 identifies the intergroup difference factors between the newly generated group and the existing group. After that, the policy decision support device 200 executes the processes in steps S205 to S206.

[0092] Next, the effects of this embodiment will be described. In this embodiment, the identification unit 240 identifies factors that satisfy the commonality criterion among multiple preconditions that satisfy the same or similar criteria, for which the prediction unit 110 has predicted future trends that meet the same or similar criteria, as group common factors. With this configuration, the policy decision support device 200 can identify group common factors that satisfy the commonality criterion among multiple preconditions. As a result, the user can recognize factors that are important to consider when deciding whether to decide on a policy implementation plan. In other words, when considering a policy implementation plan, the user does not need to examine all the factors of the preconditions, and can make a suitable decision based only on the group common factors. Furthermore, the user can suitably adopt prediction results and policy implementation plans that reflect the important factors. In this way, the policy decision support device 200 can minimize the amount of information used to consider the adoption of a policy implementation plan.

[0093] Furthermore, the identification unit 240 identifies factors that differ between a common group factor corresponding to one future trend and a common group factor corresponding to a future trend different from that one future trend, as inter-group difference factors. With this configuration, the policy decision support device 200 can identify inter-group difference factors that differ between groups. As a result, the user can recognize factors that are important for decision-making when deciding which of multiple policy implementation plans to adopt. In addition, the user can suitably adopt prediction results and policy implementation plans that reflect the important factors. In this way, the policy decision support device 100 can further minimize the amount of decision-making material used when considering the adoption of a policy implementation plan.

[0094] In this embodiment, the collection unit 150 collects information related to the factors identified by the identification unit 240. The output unit 160 outputs information indicating the factors identified by the identification unit 240 and information related to the factors collected by the collection unit 150. With this configuration, the user can obtain important factors and related information when considering a policy implementation plan.

[0095] Next, the configuration of the computer related to this disclosure will be described. Figure 6 is a block diagram illustrating the hardware configuration of computer 1000 that implements the policy decision support device 100 or policy decision support device 200. Computer 1000 is any computer. For example, computer 1000 is a stationary computer such as a personal computer or a server machine. Alternatively, computer 1000 is a portable computer such as a smartphone or a tablet terminal. Computer 1000 may be a dedicated computer designed to implement the policy decision support device 100 or policy decision support device 200, or it may be a general-purpose computer.

[0096] Computer 1000 has a processor 1001, a storage device 1002, memory 1003, a bus 1004, an input / output interface 1005, and a network interface 1006.

[0097] Processor 1001 is a variety of processing units, including CPUs (Central Processing Units), GPUs (Graphics Processing Units), FPGAs (Field-Programmable Gate Arrays), and DSPs (Digital Signal Processors).

[0098] The storage device 1002 is, for example, a non-transitory computer-readable medium. Non-transitory computer-readable media include various types of tangible storage media. Specific examples of non-transitory computer-readable media include semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM).

[0099] Memory 1003 is a main memory system implemented using RAM (Random Access Memory) or similar technologies. Memory 1003 temporarily stores data when the processor 1001 executes processing.

[0100] Bus 1004 is a data transmission path for the processor 1001, memory 1003, storage device 1002, input / output interface 1005, and network interface 1006 to send and receive data to and from each other. However, the method of connecting the processor 1001 and the others to each other is not limited to bus connection.

[0101] The input / output interface 1005 is an interface for connecting the computer 1000 with input / output devices. For example, input devices such as keyboards and output devices such as display devices are connected to the input / output interface 1005.

[0102] The network interface 1006 is an interface for connecting computer 1000 to a network. This network may be a LAN (Local Area Network) or a WAN (Wide Area Network).

[0103] The storage device 1002 stores a program that implements each functional component of the policy decision support device 100 or the policy decision support device 200. The processor 1001 reads this program into the memory 1003 and executes it to implement each functional component of the policy decision support device 100 or the policy decision support device 200.

[0104] The policy decision support device 100 or the policy decision support device 200 may be implemented by one computer 1000 or by multiple computers 1000. In the latter case, the configuration of each computer 1000 does not need to be the same and can be different.

[0105] Each functional component of the policy decision support device 100 or policy decision support device 200 may be implemented by a combination of the hardware and software described above, or by hardware (for example, hardwired electronic circuits).

[0106] Next, an overview of this disclosure will be provided. Figure 7 is a block diagram illustrating the main components of the policy decision support device. The policy decision support device 10 shown in Figure 7 (corresponding to, for example, the policy decision support device 100) includes a derivation unit 11 (implemented by a derivation unit 120 in this embodiment) that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and an identification unit 12 (implemented by an identification unit 140 in this embodiment) that identifies factors that satisfy the commonality criterion among multiple preconditions that satisfy the commonality criterion among multiple preconditions from which the policy implementation plan satisfying the same or similar criteria has been derived by the derivation unit 11, as group common factors. With this configuration, the policy decision support device 10 can identify group common factors that satisfy the commonality criterion among multiple preconditions. As a result, when the user considers whether to decide on the derived policy implementation plan, they can recognize factors that are important for making a decision. In other words, when the user considers the policy implementation plan, they do not need to scrutinize all the factors of the preconditions, and can make a suitable decision based only on the group common factors. Furthermore, users can selectively adopt prediction results and policy implementation plans that reflect important factors. In this way, the policy decision support device 10 can minimize the amount of information used to consider the adoption of a policy implementation plan.

[0107] Figure 8 is a block diagram illustrating the main components of another policy decision support device. The policy decision support device 20 shown in Figure 8 (corresponding to, for example, policy decision support device 200) includes an identification unit 21 (implemented by an identification unit 240 in this embodiment) that identifies factors that satisfy a commonality criterion among multiple different preconditions for which future trends satisfying the same or similar criteria have been predicted by a prediction unit that predicts future trends of policy parameters by applying preconditions. With this configuration, the policy decision support device 20 can identify common factors among multiple preconditions that satisfy a commonality criterion. As a result, the user can recognize factors that are important for decision-making when considering a policy implementation plan. Furthermore, the user can suitably adopt prediction results and policy implementation plans that reflect these important factors. In this way, the policy decision support device 20 can minimize the amount of decision-making material used when considering the adoption of a policy implementation plan.

[0108] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Each embodiment can be combined with other embodiments as appropriate.

[0109] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate.

[0110] Some or all of the above embodiments may also be described as follows, but are not limited to the following:

[0111] (Note 1) A derivation unit that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, The system includes an identification unit that identifies factors that satisfy the commonality criteria among multiple different preconditions from which the derivation unit has derived a policy implementation plan that satisfies the same or similar criteria, as common factors within the group. A policy decision support device characterized by the following features.

[0112] (Note 2) The identifying unit identifies factors that result in differences between the group-wide common factors corresponding to one policy implementation plan and the group-wide common factors corresponding to a policy implementation plan different from that one policy implementation plan, as inter-group difference factors. The policy decision support device described in Appendix 1.

[0113] (Note 3) The system includes a classification unit that associates the derived policy implementation plan with the assumptions applied when deriving the policy implementation plan, and classifies the assumptions associated with policy implementation plans that satisfy the same or similar criteria into the same group. The identifying unit identifies factors that satisfy the criteria for commonality among multiple preconditions classified into the same group as common factors within the group. A policy decision support device as described in Appendix 1 or Appendix 2.

[0114] (Note 4) The system includes an output unit that outputs information indicating the factors identified by the aforementioned identification unit. A policy decision support device as described in any of the appendices 1 to 3.

[0115] (Note 5) The system includes a collection unit that collects and outputs information related to the factors identified by the aforementioned identification unit. A policy decision support device as described in any of the appendices 1 through 4.

[0116] (Note 6) The system includes a prediction unit that predicts future trends of policy parameters by applying preconditions, and an identification unit that identifies factors that satisfy the commonality criteria among multiple different preconditions for which future trends satisfying the same or similar criteria are predicted, as common factors within the group. A policy decision support device characterized by the following features.

[0117] (Note 7) The identifying unit identifies factors that result in differences between a common group factor corresponding to one future trend and a common group factor corresponding to a future trend different from that one future trend as intergroup difference factors. The policy decision support device described in Appendix 6.

[0118] (Note 8) It includes a classification unit that associates predicted future trends with the assumptions applied when predicting those future trends, and classifies assumptions associated with future trends that satisfy the same or similar criteria into the same group. The identifying unit identifies factors that satisfy the criteria for commonality among multiple preconditions classified into the same group as common factors within the group. A policy decision support device as described in Appendix 6 or Appendix 7.

[0119] (Note 9) The system includes an output unit that outputs information indicating the factors identified by the aforementioned identification unit. A policy decision support device as described in any of the appendices 6 to 8.

[0120] (Note 10) The system includes a collection unit that collects and outputs information related to the factors identified by the aforementioned identification unit. A policy decision support device as described in any of the appendices 6 to 9.

[0121] (Note 11) Computers Based on the projected future trends of policy parameters using the applied assumptions, the policy implementation plan is derived. For multiple different assumptions from which a policy implementation plan satisfying the same or similar criteria has been derived, factors that satisfy the commonality criterion among these multiple assumptions are identified as common factors within the group. A method for supporting policy decision-making characterized by the following features.

[0122] (Note 12) Computers The forecasting unit predicts future trends of policy parameters by applying preconditions. For multiple different preconditions that predict future trends that satisfy the same or similar criteria, factors that satisfy the commonality criteria among these multiple preconditions are identified as common factors within the group. A method for supporting policy decision-making characterized by the following features.

[0123] (Note 13) On the computer, A derivation process that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and For multiple different preconditions from which the above derivation process has derived policy implementation plans that satisfy the same or similar criteria, the identification process identifies factors that satisfy the criteria of commonality among these multiple preconditions as common factors within the group. A program to support policy decision-making to ensure implementation.

[0124] (Note 14) On the computer, For multiple different assumptions that have been predicted to satisfy the same or similar criteria for future trends of policy parameters by applying preconditions, the identification process identifies factors that satisfy the commonality criteria among these multiple assumptions as common factors within the group. A program to support policy decision-making to ensure implementation.

[0125] Some or all of the elements (e.g., configuration and function) described in Appendices 2 to 5 that are dependent on Appendice 1 may also be dependent on Appendices 11 and 13 in the same way as those described in Appendices 2 to 5. Similarly, some or all of the elements (e.g., configuration and function) described in Appendices 7 to 10 that are dependent on Appendice 6 may also be dependent on Appendices 12 and 14 in the same way as those described in Appendices 7 to 10. Some or all of the elements described in any appendice may be applicable to various hardware, software, recording means, systems, and methods for recording software. [Explanation of Symbols]

[0126] 10,20,100,200 Policy decision support device 11 Derivation part 12,21 Specific part 110 Prediction Unit 120 Derivation part 130,230 Classification section 140,240 Specific section 150 Collection Department 160 Output section 1000 computers 1001 Processor 1002 Storage device 1003 memory 1004 Bus 1005 Input / Output Interface 1006 Network Interface

Claims

1. A derivation unit that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, The system includes an identification unit that identifies factors that satisfy the commonality criterion among multiple different preconditions from which the derivation unit has derived a policy implementation plan that satisfies the same or similar criteria, as common factors within the group. A policy decision support device characterized by the following features.

2. The specified unit identifies factors that result in differences between the group-wide common factors corresponding to one policy implementation plan and the group-wide common factors corresponding to a policy implementation plan different from that one policy implementation plan, as inter-group difference factors. A policy decision support device according to claim 1.

3. The system includes a classification unit that associates the derived policy implementation plan with the assumptions applied when deriving the policy implementation plan, and classifies the assumptions associated with policy implementation plans that satisfy the same or similar criteria into the same group. The identifying unit identifies factors that satisfy the criteria for commonality among multiple preconditions classified into the same group as common factors within the group. A policy decision support device according to claim 1 or claim 2.

4. The system includes an output unit that outputs information indicating the factors identified by the aforementioned identification unit. A policy decision support device according to claim 1 or claim 2.

5. The system includes a collection unit that collects and outputs information related to the factors identified by the aforementioned identification unit. A policy decision support device according to claim 1 or claim 2.

6. The system includes a prediction unit that predicts future trends of policy parameters by applying preconditions, and an identification unit that identifies factors that satisfy the commonality criteria among multiple different preconditions for which future trends satisfying the same or similar criteria are predicted, as common factors within the group. A policy decision support device characterized by the following features.

7. The identifying unit identifies factors that result in differences between a common group factor corresponding to one future trend and a common group factor corresponding to a future trend different from that one future trend as intergroup difference factors. The policy decision support device according to claim 6.

8. It includes a classification unit that associates predicted future trends with the assumptions applied when predicting those future trends, and classifies assumptions associated with future trends that satisfy the same or similar criteria into the same group. The identifying unit identifies factors that satisfy the criteria for commonality among multiple preconditions classified into the same group as common factors within the group. A policy decision support device according to claim 6 or claim 7.

9. Computers Based on the projected future trends of policy parameters using the applied assumptions, the policy implementation plan is derived. For multiple different assumptions from which a policy implementation plan satisfying the same or similar criteria has been derived, factors that satisfy the commonality criterion among these multiple assumptions are identified as common factors within the group. A method for supporting policy decision-making characterized by the following features.

10. On the computer, A derivation process that derives a policy implementation plan based on the future trends of policy parameters predicted by applying preconditions, and For multiple different preconditions from which the above derivation process has derived policy implementation plans that satisfy the same or similar criteria, the identification process identifies factors that satisfy the criteria of commonality among these multiple preconditions as common factors within the group. A program to support policy decision-making to ensure implementation.

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