JP6681076B2 - Entertainment interest estimation device, entertainment interest estimation method and program - Google Patents

Description

  The present invention relates to an interest estimation device, an interest estimation method, and a program for estimating the interest of a player when the player plays the game machine.

  A gaming machine typified by a pachinko machine and slot machine has a so-called hit as a result of the game played by the player playing this gaming machine, and as a result, the player feels amusement Rises. Having a large number of gaming machines with high occupancy rates, and maintaining and improving the occupancy rate of gaming machines installed in stores such as pachinko halls is a management issue for operators of this store. The operator indirectly grasps the interests felt by the player by routinely grasping the operating rate of the gaming machine.

  In addition, for the gaming machine manufacturing company, in order to improve the sales of the gaming machine, the operating rate of the gaming machine is routinely grasped, and the gaming machine manufacturing is highly interesting.

  From this point of view, the game information is received from the slot machine, the psychological state of the player is determined based on the transition of IN / OUT included in the game information of each game, the customer satisfaction score is calculated, and the customer satisfaction score is calculated. Technology for classifying members according to the number (see Patent Document 1), gaming table information and player information in a gaming facility existing in a commercial area that is a customer attraction area including own store, and game population information including an estimated maximum number of customers Furthermore, a technology (Patent Document 2) for evaluating the current market power of a game facility in a commercial area based on a current power index obtained from player information has been proposed.

JP, 2017-38728, A JP, 2002-259616, A

  In the technology described above, the interest of the player is predicted based on the operating rate of the game machine and the number of customers. However, it can be inferred that the operating rate of gaming machines is related (even indirectly) to the interest of the player, and although the operating rate is an objective number, it is directly related to the interest of the player. In other words, there is no clear relationship such as a proportional relationship between the interest of the player and the occupancy rate.

  In particular, the interests of the players are the subjective evaluations of each player, and it is highly unlikely that a clear relationship will be established with objective numbers (numerical values) such as the operating rate. .

  As a method of objectively knowing the interest of the player to a certain extent, there is a method of collecting impressions and the like when the player actually plays the game machine by a questionnaire. However, a large number of samples (players) are required to ensure objectivity in the questionnaire results, and there is a risk that the cost will be high for collecting a large number of samples.

  Therefore, it is an object of the present invention to provide an interest estimation device, an interest estimation method, and a program capable of numerically estimating the interest of a player when a player plays a particular gaming machine. Is.

To this end, playability estimating device of this invention comprises a storage unit for the solve data recorded actually occurring event during which the player certain game machine and a game is stored, it is stored in the storage unit The probability of occurrence of an event is obtained by performing a simulation of a game with a gaming machine based on the probability estimation unit that estimates the probability of occurrence of an event based on the tried data and the probability of occurrence of the event estimated by the probability estimation unit. Based on the frequency of occurrence of the event acquired by the simulation unit and the simulation unit, when the event is regarded as a combination of a notice in the reward system and a reward stochastically given based on multiple probabilities , the notice and the reward results of animal experiments by interpolating the dopamine ratio based on the relationship, by using said dopamine ratio when probability can vary from 0 to 100% By estimating the amount of dopamine that is estimated to be generated in the brain of the player when the player plays the game machine, the interest of this player when the player plays the game machine is estimated. And a dopamine amount estimation unit.

  Here, when a game machine causes a plurality of events when a player plays a game, the storage unit stores a plurality of event occurrence information relating to occurrence frequencies of the plurality of events, and the probability estimation unit determines a plurality of event occurrence information. The probability of occurrence of each of the multiple events is estimated based on the event occurrence information, and the simulation unit acquires the frequency of occurrence of each of the multiple events based on the probability of occurrence of each of the multiple events estimated by the probability estimation unit. However, the dopamine amount estimation unit may estimate the dopamine amount based on the occurrence frequency of each of the plurality of events acquired by the simulation unit.

  Further, the simulation unit acquires the expected number of coins based on the occurrence frequency of each of the plurality of events, and the dopamine amount estimation unit, the occurrence frequency and the expected number of coins of each of the plurality of events acquired by the simulation unit. The amount of dopamine may be estimated based on

  Furthermore, when a player plays a game, a single event occurs with a predetermined probability and ends, and a plurality of different events occur consecutively with a predetermined probability and end. The section may store a plurality of event occurrence information regarding the occurrence frequency of the event based on the end frequency obtained by summing the end frequency of a single event and the end frequencies of a plurality of different events.

Further, the present invention is an interest estimation method executed by an information processing device having a storage unit storing trial data in which an event actually occurred when a player plays a game with a specific game machine, in the interest estimation method. Estimate the occurrence probability of the event based on the trial data stored in, and based on the estimated occurrence probability of the event, by simulating the game by the gaming machine, the occurrence frequency of the event is acquired, Based on the frequency of occurrence, when the event was considered as a combination of a notice in the reward system and a reward given probabilistically based on multiple probabilities, the results of the animal experiment of the dopamine ratio based on the relationship between the notice and the reward interpolation to the probability is generated in the brain of the player when the player to game the game machine using said dopamine ratio when can vary from 0 to 100% By calculating the dopamine amount estimated to the player a game machine and estimates the player's interest when a game.

Furthermore, the present invention is performed in a program executed by a computer having a storage unit in which the solve data is stored which records actually occurring event during which the player certain game machine and a game, this program by a computer Then, this computer, based on the probability estimation unit that estimates the occurrence probability of the event based on the game data stored in the storage unit, and the occurrence probability of the event estimated by the probability estimation unit, By performing a simulation, a simulation unit that acquires the frequency of occurrence of an event, and based on the frequency of occurrence of the event acquired by the simulation unit, a reward that probabilistically gives an event based on a notice in the reward system and multiple probabilities Of the dopamine ratio based on the relationship between the notice and the reward when considered as a combination with By interpolating the results of the object experiments, it is estimated to the player with the dopamine ratio are generated in the brain of the player when the game of the gaming machine when the probability can vary from 0 to 100% It is characterized by causing the gaming machine to function as a dopamine amount estimation unit that estimates the interest of the player when the player plays the game by calculating the amount of dopamine.

  The interest estimation device of the present invention as described above includes a storage unit that stores event occurrence information related to the occurrence frequency of events that actually occur when a player plays a specific gaming machine, and an event stored in the storage unit. A probability estimation unit that estimates the occurrence probability of an event based on occurrence information, and a simulation that acquires the occurrence frequency of an event by performing a game simulation with a gaming machine based on the occurrence probability of the event estimated by the probability estimation unit Section and the frequency of occurrence of events acquired by the simulation section, by calculating the amount of dopamine estimated to be generated in the brain of the player when the player plays the game machine, And a dopamine amount estimation unit for estimating the interest of the player when the player plays the machine.

  With the above-described configuration, the dopamine amount estimated by the dopamine amount estimation unit is an objective that is directly related to the amount of dopamine generated in the brain of the player when the player actually plays the game machine. Is a numerical value. This makes it possible to quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Here, when the player plays a plurality of events in the gaming machine, the storage unit stores a plurality of event occurrence information regarding the occurrence frequency of the plurality of events, and the probability estimation unit is based on the plurality of event occurrence information. And estimating the respective occurrence probabilities of the plurality of events, the simulation unit acquires the respective occurrence frequencies of the plurality of events based on the respective occurrence probabilities of the plurality of events estimated by the probability estimation unit, and the dopamine amount estimation unit. However, when estimating the dopamine amount based on the occurrence frequency of each of the plurality of events acquired by the simulation unit, a direct relationship with the amount of dopamine generated in the brain of the player based on the plurality of events. Can be estimated. This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  In addition, the simulation unit acquires the expected number of coins based on the occurrence frequency of each of the plurality of events, the dopamine amount estimation unit based on the occurrence frequency of each of the plurality of events acquired by the simulation unit, and the expected number of coins Thus, when estimating the amount of dopamine, the amount of dopamine that is directly related to the amount of dopamine generated in the brain of the player based on a plurality of events can be estimated. This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Furthermore, when a player plays a game, a single event occurs and ends with a predetermined probability in the gaming machine, and a plurality of different events continuously occur and ends with a predetermined probability, and the result is stored in the storage unit. , If multiple event occurrence information regarding the event occurrence frequency based on the end frequency of a single event and the end frequency of multiple different events is stored, each event ends in a single It is possible to estimate the amount of dopamine that is directly related to the amount of dopamine produced in the brain of the player, either at the time of occurrence, or at the time of continuous occurrence and termination. This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Further, the interest estimation method of the present invention estimates the event occurrence probability based on the event occurrence information stored in the storage unit, and simulates the game by the gaming machine based on the estimated event occurrence probability. , The frequency of occurrence of the event is acquired, and the amount of dopamine estimated to be generated in the brain of the player when the player plays the game machine is calculated based on the frequency of occurrence of the acquired event. Therefore, the estimated amount of dopamine is an objective numerical value that is directly related to the amount of dopamine generated in the brain of the player when the player actually plays the game machine. This makes it possible to quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Then, the program of the present invention causes a computer to play a game based on a probability estimation unit that estimates an event occurrence probability based on event occurrence information stored in a storage unit, and an event occurrence probability estimated by the probability estimation unit. A simulation unit that obtains the frequency of occurrence of events by simulating a game using a machine, and the brain of this player when the player plays a game machine based on the frequency of occurrence of events that is acquired by the simulation unit. By calculating the amount of dopamine estimated to be generated in the game machine, the game machine is made to function as a dopamine amount estimation unit that estimates the interest of this player when the player plays the game. The amount of dopamine estimated by is the amount of dopamine generated in the brain of the player when the player actually plays the game machine. An objective numerical value has a direct relationship to the amount. This makes it possible to quantify and estimate the interest of this player when the player plays a specific gaming machine.

It is a block diagram showing a schematic structure of an interest estimation device of an example. It is a flow chart explaining an example of operation of the interest estimating device of an example. It is a figure for demonstrating an example of the principle used for the interest estimation apparatus of this invention. It is a figure for demonstrating an example of the principle used for the interest estimation apparatus of this invention.

<Principle used in the present invention>
Before describing the embodiments of the present invention, the principle used in the interest estimation apparatus of the present invention will be described with reference to FIGS. 3 and 4.

  With the recent progress in brain science, it has been found that a substance called dopamine is produced in the brain, and a specific nervous system accepts this substance to cause a pleasant sensation in humans.

  Specifically, it is known that the human and animal brains have a nervous system called a reward system that activates when the desire is satisfied or when it is found that the desire is satisfied, and gives the individual a feeling of pleasure. Has been. In mammals, the reward system is said to be the dopamine nervous system (also known as the A10 nervous system) that projects from the ventral tegmental area of the midbrain to the cerebral cortex.

  The reward system is activated not only when the desire is satisfied, but also when the person is acting in anticipation of obtaining a reward. For example, when a thirsty person drinks water, the reward system is activated in the brain and a feeling of pleasure is felt. However, if a human finds a vending machine while walking, it can be inferred that he / she can drink water at that time, so the reward system is activated at the time of discovery (above, "reward system"). , [Online], Wikipedia, [Search May 18, 2017], Internet <URL: https://ja.wikipedia.org/wiki/%E5%A0%B1%E9%85%AC%E7%B3 % BB).

  To estimate how much dopamine is actually secreted in the human brain in such a reward system, the present inventor decided to use the results of animal experiments using monkeys.

  In this experiment, an electrode was inserted into the monkey brain and the amount of dopamine when a reward juice was given was measured. We also conducted an experiment of giving a notice before giving a reward and then giving a reward. At this time, the change in the amount of dopamine when the reward was given stochastically was also measured.

  Specifically, before the reward is given, the advance notice of the reward such as the light or sound of the lamp is generated, and thereafter the action of giving the reward with a certain probability is repeatedly learned, and the relation between the advance notice of the reward and the reward The amount of dopamine under the learned sex was measured. At this time, the result shown in FIG. 3 was obtained (Wolfram Schultz, “The Reward Signal of Midbrain Dopamine Neurons”, News Physiol. Sci., (US), 1999, Vol. 14, No. 6, p. 249). -255, Wolfram Schultz, 6 others, "Explicit neural signals reflecting reward uncertainty", Phil. Trans. R. Soc. B, (UK), 2008, No.363, p.3801-3811).

  According to the results disclosed in the above paper, assuming that the dopamine value when a reward is given without prior notice is 1, the reliability of the prior notice, that is, the probability when the probability is 25%, 50%, 75%, 100%. The values are as shown in FIG. When a notice was given, two events occurred: a dopamine value that was advanced at the time of the notice and a dopamine value when the reward was actually obtained, and the ratio of the amount of dopamine secreted at that time was also found.

  Based on the results disclosed in the above-mentioned paper, the present inventor calculated that the result when a plurality of notices were repeatedly raised was as shown in FIG.

Embodiments of the present invention will be described below with reference to the drawings based on the above-described principle.
[Example]

<Schematic configuration of interest estimation device>
FIG. 1 is a block diagram showing a schematic configuration of an information processing device 10 that constitutes the interest estimation device of this embodiment.

  The information processing apparatus 10 of the present embodiment is, for example, a personal computer or the like, and includes a control unit 11, a storage unit 12, an input interface (I / F) 13 and an output interface (I / F) 14.

  The control unit 11 includes an arithmetic element such as a CPU. A control program (not shown) stored in the storage unit 12 is executed when the information processing apparatus 10 is started, and the control unit 11 controls the entire information processing apparatus 10 including the storage unit 12 based on the control program. The control is performed and the functions of the data acquisition unit 20, the probability estimation unit 21, the simulation unit 22, and the dopamine amount estimation unit 23 are executed. The operation of each of these functional units will be described later.

  The storage unit 12 includes a large-capacity storage medium such as a hard disk drive and a semiconductor storage medium such as ROM and RAM. The storage unit 12 stores the above-described control program and also temporarily stores various data required for the control operation of the control unit 11. Further, the storage unit 12 stores trial data (event occurrence information) 30.

  The trial data 30 is data obtained as a result of actually trialing a game machine that is a target for estimating and calculating the amount of dopamine. The interest estimation device 10 of the present embodiment assumes a pachinko machine as a game machine that is a target for estimating and calculating the amount of dopamine.

  When a pachinko ball is played in the pachinko machine and a pachinko ball is won in the start chucker, a lottery is started with a predetermined probability. If a pachinko ball is won in the start chucker during this lottery operation, a lottery operation is also performed for this winning. However, since the lottery operation is sequentially performed, the gaming machine stores (holds) a certain number of times even for the winning during the lottery operation. Pachinko balls win the start chucker, and a series of lottery operations are completed for the winning prizes that have been held, and the lottery results are revealed (usually, it is found by the directing operation of the (main) digital display of the gaming machine) The series of processes up to can be considered as a combination of the above-mentioned notice and reward in the reward system.

  Next, as a result of the lottery, an effect action up to the jackpot occurs with a predetermined probability. In many gaming machines, a slot is digitally displayed, and the symbol (for example, 3 × 3 symbol) displayed in this slot is in any direction (3 × 3 symbol is lateral and diagonal × 2). If they are aligned with, the transition operation to the jackpot determination is performed.

  And, in many gaming machines, this also digitally displays the effect display of the state where two symbols are aligned in either direction (this is called reach), which increases the degree of expectation for jackpot determination and the reach state. The expectation for the jackpot determination is increased by digitally displaying the notice effect operation (referred to as the reach-in-flow) from the time when the player hits the jackpot to the final jackpot determination.

  Further, before reaching the reach effect operation, an effect operation may be performed to give advance notice that this reach effect operation is performed (referred to as a pre-reach notice).

  A lottery is also performed based on a predetermined probability as to whether to shift to the reach effect operation or to the jackpot effect operation after the reach. Therefore, the pre-reach advance notice effect and the mid-reach advance notice effect can also be considered as a combination of the advance notice and the reward in the reward system described above.

  In the interest estimation device 10 of the present embodiment, the holding effect, the pre-reach notice effect, and the pre-reach flow notice effect are considered as events that occur in the gaming machine, and the situation in which the jackpot is announced 3000 times in the gaming machine is actually taken. It is generated by performing a game with a game machine, and an event generated for each game is recorded from the result of this game, and this is stored in the storage unit 12 as the game data 30.

  The attempt data 30 roughly divides the events that occurred in the attempts in which the notice of the big hits of 3000 times occurred into the holding production, the pre-reach notice production, and the notice flow of the flow during the reach. Furthermore, regarding the pre-reach notice, It is also recorded as an event whether or not a dialogue is emitted from the gaming machine and whether or not the accessory provided in the gaming machine operates. Also, regarding the flow during reach, presence or absence of advance notice action after reach, presence or absence of action of rotating symbol multiple times called pseudo-link, presence or absence of reach development action which is a staging action indicating entry into a special reach state Is also recorded as an event.

  Since what kind of event exists depends on the game machine, it goes without saying that the above example is merely an example and can be appropriately modified depending on the game machine for which the dopamine amount is estimated and calculated.

  In particular, in the present embodiment, a plurality of attempt data 30 regarding the occurrence frequencies of a plurality of events are stored, and further, based on the end frequency obtained by summing the end frequency of a single event and the end frequencies of a plurality of different events. Stores a plurality of event occurrence information related to event occurrence frequency.

  In other words, the trial data 30 of the present embodiment records the event that occurs for each trial, and also records whether or not the next event has occurred depending on the lottery result, as described above. , The plurality of trial data 30 regarding the occurrence frequency of the event based on the end frequency obtained by adding the end frequency of the single event and the end frequencies of the plurality of different events.

  The input interface 13 receives various inputs from the input device 15 connected to the information processing device 10 and outputs them to the control unit 11. The input device 15 of this embodiment is, for example, a keyboard, a mouse, or the like, and is capable of inputting coordinate designations on a display screen of a display device 16 described later.

  The output interface 14 receives the output signal output from the control unit 11 and outputs it to the display device 16 and the printing device 17. The display device 16 of this embodiment is, for example, a liquid crystal display device, and displays a display screen on a display surface (not shown) based on a display control signal output via the output interface 14. The printing device 17 of this embodiment is, for example, a printer, and prints a predetermined character or image based on a print control signal output via the output interface 14.

  Next, each functional unit configured in the control unit 11 will be described.

  The data acquisition unit 20 reads the attempt data 30 stored in the storage unit 12 and provides it to the probability estimation unit 21. In particular, since the trial data 30 of the present embodiment is the trial data 30 related to a plurality of events, the data acquisition unit 20 reads the plurality of trial data 30 and provides them to the probability estimation unit 21.

  The probability estimation unit 21 estimates the occurrence probability of an event based on the attempt data 30 stored in the storage unit 12 and provided from the data acquisition unit 20. In particular, the probability estimation unit 21 of the present embodiment estimates the respective occurrence probabilities of a plurality of events based on the plurality of attempt data 30.

  The simulation unit 22 acquires the event occurrence frequency by simulating the game by the gaming machine based on the event occurrence probability estimated by the probability estimating unit 21.

  In particular, the simulation unit 22 of the present embodiment acquires the respective occurrence frequencies of the plurality of events based on the respective occurrence probabilities of the plurality of events estimated by the probability estimation unit 21. Further, the simulation unit 22 acquires the expected payout number based on the occurrence frequency of each of the plurality of events.

  The dopamine amount estimation unit 23 calculates the amount of dopamine estimated to be generated in the brain of the player when the player plays the game machine, based on the occurrence frequency of the event acquired by the simulation unit 22. By doing so, the interest of this player when the player plays the game machine is estimated.

  In particular, the dopamine amount estimation unit 23 of the present embodiment estimates the dopamine amount based on the occurrence frequency of each of the plurality of events acquired by the simulation unit 22. In addition, the dopamine amount estimation unit 23 estimates the dopamine amount based on the occurrence frequency of each of the plurality of events acquired by the simulation unit 22 and the expected number of coins.

  Details of operations of the data acquisition unit 20, the probability estimation unit 21, the simulation unit 22, and the dopamine amount estimation unit 23 will be described later.

<Operation of interest estimation device>
Next, the operation of the interest estimation device 10 of the present exemplary embodiment will be described with reference to the flowchart of FIG.

  When the operation of the interest estimation device 10 is started, first, in step S10, the data acquisition unit 20 of the control unit 11 reads the attempt data 30 stored in the storage unit 12 and provides it to the probability estimation unit 21. To do.

  In step S <b> 11, the probability estimation unit 21 of the control unit 11 estimates the event occurrence probability based on the attempt data 30 provided by the data acquisition unit 20.

  Here, the probability of occurrence of each event is often preset by the gaming machine manufacturer, and the interest estimating device 10 of the present embodiment also knows the probability of occurrence of each event set by the gaming machine manufacturer. If so, the dopamine amount estimated by the dopamine amount estimation unit 23 can be more accurate. However, since it is not always possible to know the occurrence probability of each event set by the gaming machine manufacturing company, the interest estimation device 10 of the present embodiment uses the trial data 30 obtained as a result of actually performing a trial on the gaming machine. The probability of occurrence of each of a plurality of events is estimated based on.

  Here, what is referred to as “estimation” is the true occurrence probability of each event set by the gaming machine manufacturer as described above, and the occurrence probability of each event obtained from the attempt data 30 is estimated only. It is indicated that it is the generated occurrence probability.

  Next, in step S12, the simulation unit 22 of the control unit 11 performs a game simulation of the gaming machine based on the event occurrence probability estimated by the probability estimation unit 21 to obtain the event occurrence frequency.

  The trial data 30 is the occurrence frequency of each event in the situation where 3000 big notices of big hits occur, and the probability estimation unit 21 estimates the occurrence probability of each event based on the trial data 30. However, from the viewpoint of obtaining a more accurate occurrence probability, in the interest estimation device 10 of the present embodiment, the simulation unit 22 simulates a game in order to artificially perform a larger number of trials.

  The dopamine amount estimated by the dopamine amount estimation unit 23 becomes a random variable, and its value follows a certain probability distribution. In addition, this value depends on the number of times that a situation in which a big hit notice called a start number occurs occurs.

  Therefore, in the interest estimation device 10 of the present embodiment, the simulation unit 22 performs 1 million simulations with the number of start times of 150 that is guided in general game time and game amount as the number of start times of this time, and the simulation unit 22 performs the simulation. The probability distribution of the dopamine amount of the gaming machine was numerically obtained by estimating it with the dopamine amount estimating unit 23.

  In the simulation operation performed by the simulation unit 22 in step S12, the winning probability is unified to 1/320. This is because the probability of hitting may differ for each gaming machine, and if the dopamine amount estimating operation by the dopamine amount estimating unit 23 is performed with the probability of hitting different, it is difficult to make an objective comparison for each gaming machine. This is because.

  Next, in step S13, based on the occurrence frequency of the event obtained by the simulation unit 22, the dopamine amount estimation unit 23 of the control unit 11 puts it in the brain of the player when the player plays the game machine. By calculating the amount of dopamine that is estimated to be generated, the interest of this player when the player plays the game machine is estimated.

The dopamine amount estimation unit 23 of the present embodiment estimates the dopamine ratio in the following four events.

・ Dopamine ratio by holding ball (value to use: probability of holding, reliability)
・ Dopamine ratio based on pre-reach notice (value to be used: probability of occurrence of each pre-reach notice, its reliability)
・ Dopamine ratio due to mid-reach flow (values used: pseudo-relation, advance notice after reach, probability of reach development and development probability, its reliability)
・ Total dopamine ratio = total dopamine ratio of the above three

Here, the reliability of each item represents the probability of a big hit when the notice is given.

Moreover, in the animal experiment shown in FIG. 3 , only the dopamine ratios with the reliability of 0%, 25%, 50%, 75%, 100% were given, but the dopamine ratios with other probabilities were linear. It was calculated using interpolation. At this time, each dopamine ratio (DA) was given by the following method.

・ DA of held ball = DA of held ball + DA of jackpot
・ DA = prior to reach
max (others / serif DA + jackpot DA, others / character DA + jackpot DA, ...)
・ DA during the reach flow = f (DA of the notice after the reach) × DA of pseudo-ream
+ F (DA of reach development) DA of advance notice after reach
+ DA of reach development + DA of jackpot
・ Total DA = Reserved ball DA + Reach advance notice DA + Reaching flow DA

However, max (x, y ....) is a function that returns the maximum value of the variable in parentheses,
f (x) is a function that returns 1 if x is 1 or more, and returns the value of x if x is less than 1.

  Here, the DA of the mid-reach flow is an expression that takes into consideration the time history of each event in the mid-reach flow. This is because the events within the reach flow often occur in steps, and these events are considered as expected as described in the above-mentioned principle. Moreover, the reason why the number of events during the reach is three is based on the knowledge of the brain science that the brain generally has three lumps of expectation.

Using these formulas, the respective dopamine ratio and the total dopamine ratio were calculated. Further, the value obtained by multiplying the total dopamine ratio by the expected payout is defined as the amount of dopamine in the gaming machine here.

Amount of dopamine on game machines = total DA x expected payout

Here, the expected payout represents the expected value of the payout obtained when the jackpot is drawn.

  Also, in order to achieve consistency with the animal experiments introduced by the above-mentioned principle, it is assumed that the player has learned the held ball, the gimmick of a role object, and the reliability of each performance. .

  The dopamine amount calculated by the dopamine amount estimating unit 23 in this way is the dopamine amount estimated to be generated in the brain of the player when the player plays the game machine, and this dopamine The amount can be used to estimate the interest that the player will feel when he plays the gaming machine.

Then, in step S14, the control unit 11 outputs the dopamine amount calculated by the dopamine amount estimation unit 23 in step S13 to the display device 16 and the printing device 17 via the output interface 14.
<Effects of this embodiment>

  As described above, the interest estimation device 10 of the present invention includes the storage unit 12 that stores event occurrence information related to the occurrence frequency of events that actually occur when a player plays a specific gaming machine, and an event occurrence. A probability estimation unit 21 that estimates the occurrence probability of an event based on information, a simulation unit 22 that acquires the occurrence frequency of an event by performing a game simulation by a gaming machine based on the occurrence probability of an event, and an occurrence of the event By calculating the amount of dopamine that is estimated to be generated in the brain of the player when the player plays the game machine based on the frequency, Since the dopamine amount estimating unit 23 for estimating the interest is included, the amount of dopamine estimated by the dopamine amount estimating unit 23 is actually a game played by the player. An objective numerical value has a direct relationship to dopamine amount produced in the brain of the player when. This makes it possible to quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Here, a plurality of events occur in the gaming machine when the player plays a game, a plurality of event occurrence information relating to the occurrence frequencies of the plurality of events are stored in the storage unit 12, and the probability estimation unit 21 generates a plurality of event occurrences. The occurrence probability of each of the plurality of events is estimated based on the information, the simulation unit 22 acquires the occurrence frequency of each of the plurality of events based on the occurrence probability of each of the plurality of events, and the dopamine amount estimation unit 23 determines the plurality of occurrence frequencies. Since the amount of dopamine is estimated based on the frequency of occurrence of each event, it is possible to estimate the amount of dopamine that is directly related to the amount of dopamine produced in the brain of the player based on multiple events. . This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  In addition, the simulation unit 22 acquires the expected payout number based on the occurrence frequency of each of the plurality of events, and the dopamine amount estimation unit 23 determines the dopamine amount based on the occurrence frequency of each of the plurality of events and the expected payout number. Since it is estimated, it is possible to estimate the amount of dopamine which is directly related to the amount of dopamine generated in the brain of the player based on a plurality of events. This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  Further, when the player plays a game, a single event occurs and ends with a predetermined probability in the gaming machine, and a plurality of different events continuously occur and ends with a predetermined probability, and the storage unit 12 Stores multiple event occurrence information related to the event occurrence frequency based on the end frequency of a single event and the end frequency of multiple different events, so each event ends in a single It is possible to estimate the amount of dopamine that is directly related to the amount of dopamine produced in the brain of the player both when playing and when it continuously occurs and ends. This makes it possible to more specifically quantify and estimate the interest of this player when the player plays a specific gaming machine.

  In addition, according to the interest inferring apparatus of the present embodiment, the player can feel that this game machine is actually installed in a hall or the like and played by the player with respect to the game machine before being sold. You can evaluate the interests in advance. Thereby, the gaming machine manufacturer can adjust the gaming machine to make the player feel more interesting by checking the configuration of the event and the probability structure thereof.

  In addition, it is possible for the gaming machine manufacturer to keep the development cost of the gaming machine at an appropriate level by being able to objectively grasp the interest. In addition, the gaming machine manufacturing company can accurately grasp the selling point of the gaming machine that is likely to be interesting.

  In addition, regarding gaming machines already installed in halls, etc., it is possible to objectively grasp the size of the interest with other gaming machines, and propose efficient operation to hall operators, etc. be able to.

On the other hand, the interest estimation device of the present embodiment does not estimate the brand power and content power of the gaming machine, which may affect the actual operation data, and the overall market condition and seasonal variability. In other words, if there is a tendency that there is no explanation between the interest of the player estimated by the interest estimating device of the present embodiment and the actual operation data, that tendency is due to the brand power of the gaming machine described above. Can be guessed to be. In other words, the possibility of digitizing the brand power and the like of this gaming machine can be expanded by using the estimation result by the interest estimation device of this embodiment as a starting point.
[Experimental example]
Using the interest estimation device 10 of the present embodiment, the dopamine ratio in the above-mentioned four events was estimated for three actual types of gaming machines.

The probability distribution of the dopamine ratio for each simulation was obtained by the dopamine amount estimation unit 23, and the median value was multiplied by the expected number of balls to estimate the dopamine amount. Here, the median value was used in the evaluation, because the variation in the amount of dopamine estimated in each simulation is large, so if the evaluation is performed with the average value, the average value is pulled by the data with the large value of the dopamine amount. Because. If evaluated with the median value, it can be inferred that more than half of the players who have played the game may have had an interest above the median value. From this calculation result, the interest that the player will feel when playing a game machine is

B ＞ C ＞ A

Was estimated to be.

  Next, it was confirmed whether this estimation result matches the actual game data. As the actual game data used in this experimental example, a total value of operation data of nationwide halls called DK-SIS provided by Daikoku Denki Co., Ltd. was used. The data used are "out of the first week" and "out of the second week" of each model. Here, out represents the number of balls hit by the gaming machine, and the larger the out, the more the gaming machine is playing. The “out of the first week” and “out of the second week” used here are national averages, not totals.

These values were used to calculate the next rate of decline.

Falling rate = 2nd week out / 1st week out

  Here, if the descending rate is simply considered, it can be grasped as a possibility, a probability, or a ratio of a player who played in the first week to play in the second week. In general, the operation of game machines on the market is highest during the first week and decreases after the second week. At this time, there are various decreasing tendencies such as a sharp decrease and a gradual decrease.

At this time, this rate of decline can be regarded as one indicator of enjoyment. This is because if the gaming machine is fun, it will be played many times, which will reduce the decrease in the outing of the second week. In this way, the enjoyment of each gaming machine based on the operating data of the gaming machine based on the processing rate

B ＞ C ＞ A

This is in the order of, which is in agreement with the previous estimation result. As a result, it can be seen that the interest estimating device 10 of the present embodiment correctly estimates the interest when the player actually plays the game machine.
(Other)

  The interest estimation apparatus of the present invention is not limited in details to the above-described embodiment, and can be appropriately changed within the scope of the present invention. As an example, in the above-described embodiment, the interest of pachinko as a gaming machine was estimated, but the interest that can be estimated by the interest estimating device of the present invention is not limited to that of pachinko, and pachislot and slot machines, and even card games. It is possible to estimate even the interest of social games.

  Although the amount of dopamine was estimated by the interest estimation device of the example, other substances such as GABA (γ-aminobutyric acid: γ (gamma) -amino butyric acid) can be estimated as a reward system. is there.

  Further, in the above-mentioned embodiment, the reliability (that is, probability) other than the reliability actually performed in the animal experiment introduced in the principle was obtained by using linear interpolation, but other interpolation methods, for example, polynomial The reliability may be obtained by interpolation or spline interpolation. In addition, fine adjustment may be performed without diverting the results of animal experiments.

  Furthermore, the calculation used for the estimation of the amount of dopamine is an example, and other calculation methods can be suitably applied. As an example, the total value of the dopamine ratio for each event is used in the above-described embodiment, but various methods such as weighted average, linear model / non-linear model, and neural network can be applied.

Further, in the above-described embodiment, the explanation has been made on the assumption that there is some relationship between the operation of the gaming machine, the number of units sold, and the interest of the gaming machine. If this is more generally considered,

Gaming machine evaluation = g (joy of gaming machine, etc.)

Can be expressed as Here, g (·) represents an appropriate function, and various functions can be applied. These numbers can be divided into internal factors and external factors.

Gaming machine evaluation = Internal factors + External factors

  At this time, the internal factor represents a factor that the gaming machine has. For example, the jackpot probability of a game machine, the content power of the work used for the game machine, the brand power of the game machine development maker, and the popularity of the previous work in the case of a series machine having a previous work may be considered.

  In addition, external factors represent those that affect the evaluation other than the performance of the gaming machine. For example, countermeasures within the industry regarding seasonal fluctuations, economic conditions, social conditions, and emissivity can be considered, and these are factors that cannot be operated from a gaming machine.

However, these items can also be considered as conditions that affect all gaming machines operating or sold at the same time. Under these assumptions, external factors can be considered as common terms for each gaming machine when comparing gaming machines for the same period or for a short period of time, and it is internal factors that determine the relative evaluation of gaming machines. Become.

Relative evaluation of game machines = internal factors

Therefore, it is important to examine the internal factors when comparing game machines. The internal factors are considered to be all the elements that make up the platform, and for example, it is possible to disassemble each and every component used in the platform and capture them in detail, or to roughly capture them only by paying attention to the jackpot probability. . For example, here, the internal factors of the gaming machine can be understood as follows.

Internal factor of gaming machine = f (content, brand, gaming machine performance, ...)
≒ f (content, brand, game machine performance)

Here, the content is a subject used in a game machine, and an animation, a drama, or a character originally developed by a developer is used. The brand means a series image when the game machine is a series machine, and when the game machine is developed by a famous manufacturer, a stand image other than content such as a manufacturer brand.

  At this time, it may be difficult to separate the content from the series brand. The gaming machine performance represents the elements of the gaming machine excluding the content and brand, and is an element that does not depend on the content or brand. For example, the jackpot probability. In fact, gaming machines with only the jackpot probability changed are sold.

  Factors that do not depend on the content or brand are the probability of jackpots and the probability of reaching the jackpot probability, the ball output performance, the play method of the game machine, the intensity of the light emitted from the game machine, and the volume of the sound. To be Further, f (•) represents an appropriate function, and various functions can be applied. By analyzing in such a form, it is possible to estimate a portion other than the enjoyment of the gaming machine and to adjust the optimal gaming machine performance.

  In the above-described embodiment, the program for operating the interest estimating device 10 is stored in the storage unit 12 and provided, but a DVD (Digital Versatile) in which the program is stored is stored using an optical disk drive (not shown). Disc), a USB external storage device, a memory card, or the like, and the program may be read from the DVD or the like into the interest estimating device 10 and operated. Alternatively, the program may be stored in a server device on the Internet, and the interest estimating device 10 may be provided with a communication unit to read the program into the interest estimating device 10 to operate. Further, in the above-described embodiment, the interest estimation device 10 is composed of a plurality of hardware elements, but it is also possible for the control unit 11 to realize some operations of these hardware elements by the operation of a program. .

10 Information processing device (entertainment device)
11 control unit 12 storage unit 20 data acquisition unit 21 probability estimation unit 22 simulation unit 23 dopamine amount estimation unit 30 trial and trick data

Claims (6)

A storage unit for the solve data is player specific gaming machine was recorded actually occurring event upon game is stored,
A probability estimation unit that estimates the occurrence probability of the event based on the trial data stored in the storage unit;
A simulation unit that acquires the occurrence frequency of the event by performing a game simulation by the gaming machine based on the occurrence probability of the event estimated by the probability estimation unit,
Based on the frequency of occurrence of the event acquired by the simulation unit, when the event is regarded as a combination of a notice in the reward system and a reward stochastically given based on a plurality of probabilities, the notice and the reward The result of the animal experiment of the dopamine ratio based on the relationship with is interpolated, and when the player plays the game machine using the dopamine ratio when the probability can change from 0 to 100% , this game A dopamine amount estimation unit for estimating the interest of the player when the player plays the game machine by calculating the amount of dopamine estimated to be generated in the brain of the player. The interest estimation device. In the gaming machine, a plurality of the events occur when the player plays a game,
The storage unit stores a plurality of the trial data regarding the occurrence frequency of the plurality of events,
The probability estimating unit estimates the respective occurrence probabilities of the plurality of events based on the plurality of trial data ,
The simulation unit, based on the occurrence probability of each of the plurality of events estimated by the probability estimation unit, acquires the occurrence frequency of each of the plurality of events,
The interest estimation apparatus according to claim 1, wherein the dopamine amount estimation unit estimates the dopamine amount based on the occurrence frequency of each of the plurality of events acquired by the simulation unit. The simulation unit acquires an expected number of coins based on the occurrence frequency of each of the plurality of events,
The said dopamine amount estimation part estimates the said dopamine amount based on each occurrence frequency of the said some event obtained by the said simulation part, and the said expected payout number, The dopamine amount is estimated. Of interest estimation device. In the gaming machine, when the player plays a game, the single event occurs and ends with a predetermined probability, and a plurality of different events continuously occur and ends with a predetermined probability,
The storage unit stores a plurality of pieces of the attempt data regarding an occurrence frequency of the event based on an end frequency obtained by adding an end frequency of a single event and an end frequency of a plurality of different events. The interest estimation device according to claim 2 or 3. A interest estimating method executed by an information processing apparatus having a storage unit in which the solve data is stored by the player and recorded actually occurring event upon game specific gaming machine,
The probability of occurrence of the event is estimated based on the trial data stored in the storage unit, and the frequency of occurrence of the event is calculated by performing a game simulation by the gaming machine based on the estimated probability of occurrence of the event. To get
Based on the occurrence frequency of the acquired event, based on the relationship between the notice and the reward when the event is considered as a combination of the notice in the reward system and the reward stochastically given based on a plurality of probabilities. By interpolating the result of the animal experiment of the dopamine ratio and using the dopamine ratio when the probability can be changed from 0 to 100%, when the player plays the game machine, it is stored in the brain of the player. An interest estimation method, wherein the interest of the player when the player plays the game machine is estimated by calculating the amount of dopamine estimated to be generated. A program executed by a computer having a storage unit in which the solve data is stored by the player and recorded actually occurring event upon game specific gaming machine,
When this program is executed by the computer,
A probability estimation unit that estimates the occurrence probability of the event based on the trial data stored in the storage unit;
A simulation unit that acquires the occurrence frequency of the event by performing a game simulation by the gaming machine based on the occurrence probability of the event estimated by the probability estimation unit,
Based on the frequency of occurrence of the event acquired by the simulation unit, when the event is regarded as a combination of a notice in the reward system and a reward stochastically given based on a plurality of probabilities, the notice and the reward The result of the animal experiment of the dopamine ratio based on the relationship with is interpolated, and when the player plays the game machine using the dopamine ratio when the probability can change from 0 to 100% , this game By calculating the amount of dopamine estimated to be generated in the brain of the player, the game machine is caused to function as a dopamine amount estimation unit for estimating the interest of the player when the player plays the game. And the program.