CN111729316A - Card-out recommendation method and system in card battle game and game terminal - Google Patents

Card-out recommendation method and system in card battle game and game terminal Download PDF

Info

Publication number
CN111729316A
CN111729316A CN202010540908.7A CN202010540908A CN111729316A CN 111729316 A CN111729316 A CN 111729316A CN 202010540908 A CN202010540908 A CN 202010540908A CN 111729316 A CN111729316 A CN 111729316A
Authority
CN
China
Prior art keywords
card
cards
category
player
game
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010540908.7A
Other languages
Chinese (zh)
Other versions
CN111729316B (en
Inventor
高运
王恺
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing ELEX Technology Co Ltd
Original Assignee
Beijing ELEX Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing ELEX Technology Co Ltd filed Critical Beijing ELEX Technology Co Ltd
Priority to CN202010540908.7A priority Critical patent/CN111729316B/en
Publication of CN111729316A publication Critical patent/CN111729316A/en
Application granted granted Critical
Publication of CN111729316B publication Critical patent/CN111729316B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/70—Game security or game management aspects
    • A63F13/79—Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/80—Special adaptations for executing a specific game genre or game mode
    • A63F13/822—Strategy games; Role-playing games
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/80—Special adaptations for executing a specific game genre or game mode
    • A63F13/843—Special adaptations for executing a specific game genre or game mode involving concurrently two or more players on the same game device, e.g. requiring the use of a plurality of controllers or of a specific view of game data for each player
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
    • A63F2300/55—Details of game data or player data management
    • A63F2300/5546—Details of game data or player data management using player registration data, e.g. identification, account, preferences, game history

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Business, Economics & Management (AREA)
  • Computer Security & Cryptography (AREA)
  • General Business, Economics & Management (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention belongs to the technical field of card mobile games, and discloses a card-out recommendation method, a system and a game terminal in a card battle game, wherein the recommendation method comprises the following steps: in a game terminal, identifying a current game scene; when the current game scene is a first preset game scene, acquiring the category of cards in the current game and the remaining number of the cards in each category; calculating the category probability of the player for obtaining the next card according to the remaining number of cards in each category; obtaining cards currently owned by the player, and recommending card playing based on the category probability of the next card obtained by the player; wherein: the categories are classified based on the rules of the current game and/or the self definition of the player; in conclusion, the player can play cards by referring to the upper player and play cards based on the cards to be acquired, so that the reference range and flexibility of playing cards of the player are improved, and the game experience is improved.

Description

Card-out recommendation method and system in card battle game and game terminal
Technical Field
The invention belongs to the technical field of card mobile games, and particularly relates to a card-out recommendation method and system in a card battle game and a game terminal.
Background
With the rapid development of mobile electronic devices, more and more applications can be installed and run on the mobile electronic devices. Among them, the mobile game is one of the important ways of entertainment in people's life at various stages by virtue of its dazzling animation effect and excellent game experience.
In the existing mobile phone games, card battle games are very common game types; currently, in the process of executing card battles, most current players play cards according to the types of the cards played by the players, and after playing cards, the game system randomly supplements a card to the current players until the cards are supplemented or a certain banked player dies, and the game is finished. In the above-mentioned card-playing modes, the current player can only select the playing card according to the historical playing card state, which has great limitation, and especially for the novice player, the selection of the playing card is difficult to grasp, and the game experience is influenced.
Disclosure of Invention
In view of the above, the present invention provides a card-out recommendation method, system and game terminal in a card-match game, so as to achieve the effect of effectively solving the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a card-out recommendation method in a card battle game relates to a game terminal installed and operated with the card battle game, and is applied to the game terminal and comprises the following steps:
in the game terminal, identifying a current game scene;
when the current game scene is a first preset game scene, acquiring the category of cards in the current game and the remaining number of the cards in each category;
calculating the category probability of the player for obtaining the next card according to the remaining number of cards in each category;
obtaining cards currently owned by the player, and recommending card playing based on the category probability of the next card obtained by the player;
wherein:
the categories are categorized based on the current game's own rules and/or player customizations.
Preferably, the first predetermined game scene is a scene in which the player is to play cards.
Preferably, after identifying the current game scene, the method further comprises: when the current game scene is a second preset game scene, identifying whether cards acting on the second preset game scene exist in the cards currently owned by the player; if yes, conducting card playing recommendation according to the second preset game scene; otherwise, the game continues.
Preferably, the second predetermined game scenario is a scenario in which the player is attacked.
Preferably, when the probability of the category to which the player has obtained the next card is calculated: ptN/M; wherein t is any one of all categories, P is the probability that the next card acquired by the player belongs to the category t, N is the remaining number of cards in the category t, and M is the remaining total number of cards in all the categories.
Preferably, when the card-out recommendation is made:
identifying categories of cards currently owned by the player and the number of cards in each category;
supplementing the counting cards to the player at least once, and determining the occupation ratio of each category in the calculation basis by taking the counting cards and the currently owned cards as the calculation basis;
and executing card-playing recommendation based on the high and low of the occupation ratio, and recommending cards in the category with the highest occupation ratio when executing the card-playing recommendation.
Further, when supplementing the player with the count cards: preferably, the probability of the category to which the player obtains the next card is ranked from high to low, and the category of the calculated card is determined based on the preferred ranking.
Further, when the player is replenished with the counting card N times:
Wt＝M1*P1+……+MN*PN(ii) a Wherein:
t is any one of all categories, WtTo perform the total percentage of category t after N additions of cards, M1……MNFor performing N card additions a single occupation ratio, P, of category t1……PNThe category probability corresponding to each counting card when the N times of the supplement of the counting cards are executed;
n is any integer of 1 … … N;
MNQ/E; wherein:
MNthe single occupation ratio of the category t when the N-th card counting replenishment is executed is Q, and the number of cards under the category t in the calculation basis when the N-th card counting replenishment is executed is Q; e is the total card amount in the calculation basis when the Nth card counting supplement is executed.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, cards in the game are classified, the category probability of obtaining the next card by a player after the player plays the cards is calculated according to the card classification, and then feedback type optimal recommendation is carried out on the current playing card based on the probability, so that the player can play the cards by referring to an upper player and can play the cards based on the cards to be obtained, the reference range and flexibility of playing the cards by the player are improved, and the game experience is improved.
In the preferred recommendation, the method is carried out on the basis of the card types currently owned by the players, so that the balance of the card types currently owned by the players can be effectively ensured, the players can effectively deal with different conditions in the game, the effect of improving the winning probability of the battle is further achieved, and the game experience is improved.
In order to achieve the above purpose, the invention also provides the following technical scheme:
a card-deal recommendation system in a card-fighting game, comprising:
the game system comprises an identification module, a processing module and a processing module, wherein the identification module is used for identifying whether a current game scene is a preset game scene in a game terminal, and the preset game scene at least comprises a first preset game scene;
the acquisition module is used for responding to the identification result of the identification module and acquiring the category of the cards in the game and the remaining number of the cards in each category;
the calculating module is used for calculating the category probability of the player for obtaining the next card according to the obtaining result of the obtaining module;
and the preference and recommendation module is used for acquiring cards currently owned by the players and recommending the cards in a playing way by combining the calculation results of the calculation module.
A gaming terminal comprising a memory and a processor; the storage is stored with at least one executable code; the at least one executable code is loaded and executed by the processor, and when loaded and executed, the at least one executable code implements the disclosed card dealing recommendation method.
Drawings
FIG. 1 is a flow chart of a card deal recommendation method provided by the present invention;
fig. 2 is a block diagram of a card-deal recommendation system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a card-out recommendation method in a card battle game, and particularly relates to a game terminal provided with and running the card battle game, wherein the game terminal can be formed by intelligent mobile terminals such as a mobile phone and an IPAD (Internet protocol digital assistant);
when the card battle type game is operated, the game at least comprises two battle parties, and the at least two battle parties participate in game battle by corresponding game terminals.
The following detailed description of the card-playing recommendation method using one of the competitors as the first-person perspective includes the following embodiments:
example 1
In this embodiment, a method for recommending a card deal in a card-match game is executed by the game terminal.
Specifically, please refer to fig. 1, which is a flowchart illustrating a card-out recommending method in a card-game match-up game disclosed in the present embodiment, wherein the card-out recommending method specifically includes the following steps:
s1, identifying a current game scene in a game terminal;
s2, when the current game scene is a first preset game scene, obtaining the category of cards in the current game and the remaining number of the cards in each category;
in particular, in the present embodiment, it may be preferable for the first predetermined game scene that the player is in a scene of cards to be dealt. Therefore, the player enters the card-playing recommendation mode when a game scene to be played appears in the game process, and the category of the cards in the current game and the residual number of the cards in each category are acquired firstly in the mode;
where the categories for the cards are categorized based on the rules and/or player customizations of the current game itself. As is easily explained, in a card battle game such as sanguo, cards can be classified into: attack class 'killing' cards, defense class 'flashing' cards, brocade class 'delay' cards, rescue class 'peaches' cards and the like. In addition, customized classifications may also be made based on the player's own gaming habits, and are explained in detail below for ease of description and understanding in terms of defining classifications:
the custom classification is: a first class A, a second class B, a third class C and a fourth class D;
for example, under this custom classification, let:
in the card game 01, four players are present per game a/b/c/d, and are sequentially dealt in the order of a/b/c/d, and the total number of cards contained in each game is 100, and at the start of the game, 5 cards are allocated to each player as a play basis, whereby the following data are proposed:
the total number of the cards in the first category A is 5, and 0 card is randomly distributed to the players when the game is started, so that the remaining number of the cards in the first category A is 5;
the total number of the cards in the second category B is 30, 5 cards are randomly distributed to the players when the game is started, and the remaining number of the cards in the second category B is 25;
the total number of the cards in the third category C is 50, 12 cards are randomly distributed to the players when the game is started, and the remaining number of the cards in the third category C is 38;
the total number of cards in the fourth category D is 15, and if 3 cards are randomly allocated to the player at the start of the game, the remaining number of cards in the fourth category D is 12.
S3, calculating the category probability of the player for obtaining the next card according to the remaining number of the cards in each category;
specifically, in this embodiment, the calculation of the probability of the category to which the player obtains the next card is performed in the following manner: ptN/M; wherein t is any one of all categories, P is the probability that the next card acquired by the player belongs to the category t, N is the remaining number of cards in the category t, and M is the remaining total number of cards in all the categories.
Thus, continuing with the above-described setting example, the following calculation results are obtained:
with respect to the first category a: pt(A)＝N/M＝5/(5+25+38+12)＝5/80＝6.25％；
With respect to the second category B: pt(B)＝N/M＝25/(5+25+38+12)＝25/80＝31.25％；
With respect to the third category C: pt(C)＝N/M＝38/(5+25+38+12)＝38/80＝47.5％；
With respect to the fourth category D: pt(D)＝N/M＝12/(5+25+38+12)＝12/80＝15％。
In summary, after a player plays a card in a scene of a card to be played, the probability of obtaining the card in the first category a is 6.25%; the probability of obtaining a card under the second category B is 31.25%; the probability of obtaining cards in the third category C is 47.5%; the probability of acquiring a card under the fourth category D is 15%.
S4, obtaining a card currently owned by the player, and recommending card playing based on the category probability of the next card obtained by the player;
specifically, in this embodiment, regarding the card-playing recommendation, the specific way is:
s41, identifying the type of cards currently owned by a player and the number of cards in each type;
for example, in the present embodiment, player a is described as the first-person perspective; suppose that player a currently owns a card comprising:
first class a: 0 sheet; second class B: 2, placing the sheets;
the third category C: 1, 1 sheet; the fourth category D: 2 pieces of the Chinese herbal medicine.
S42, supplementing the counting cards to the player at least once, and determining the occupation ratio of each category in the calculation basis by taking the counting cards and the cards owned by the player at present as the calculation basis;
more specifically, in the present embodiment, when supplementing player a with the calculation cards: preferably sorting the probability of the category to which the player obtains the next card from high to low, and determining the category of the cards based on the preferred sorting;
in summary, the preferred ranking of the probability of the category to which the player has captured the next card is: third class C/second class B/fourth class D/first class a. It can be seen that, when the card is first replenished, the card type is the third type C.
Correspondingly, after a third category C of house cards is added, player a will have the following base of calculation: 0 sheet (A); 2 sheets (B); 2 sheets (C); 2 sheets (D); on the basis of the calculation, the single occupation ratio of the cards of each category is obtained:
with respect to the first category a: mN(A1)＝Q/E＝0/(0+2+2+2)＝0；
With respect to the second category B: mN(B1)＝Q/E＝2/(0+2+2+2)＝1/3；
With respect to the third category C: mN(C1)＝Q/E＝2/(0+2+2+2)＝1/3；
With respect to the fourth category D: mN(D1)＝Q/E＝2/(0+2+2+2)＝1/3。
As can be seen from the above, after the first calculation of the single occupation ratio (hereinafter, referred to as the first single occupation ratio) is performed, the first single occupation ratios of the second category B cards and the fourth category D cards are the same, and at this time, the second supplementary calculation of the cards is performed, and the second calculation of the single occupation ratio is also performed correspondingly.
When the second card adding is performed, the determination of the category of the cards is also performed according to the above preferred rank, and the category of the cards determined this time should be the second category B.
Correspondingly, after replenishing a second category B of house cards, player a will have the following base of calculation: 0 sheet (A); 3 sheets (B); 1 sheet (C); 2 sheets (D); on the basis of the calculation, the single occupation ratio of the cards of each category is obtained:
with respect to the first category a: mN(A2)＝Q/E＝0/(0+3+1+2)＝0；
With respect to the second category B: mN(B2)＝Q/E＝3/(0+3+1+2)＝1/2；
With respect to the third category C: mN(C2)＝Q/E＝1/(0+3+1+2)＝1/6；
With respect to the fourth category D: mN(D2)＝Q/E＝2/(0+3+1+2)＝1/3。
As can be seen from the above, the category with the highest second single occupancy acquired after the second single occupancy is executed is the second category B. On the basis, the integrated calculation of the first single occupation ratio and the second single occupation ratio is also carried out to obtain the total occupation ratio of the cards of each category after the supplementation of the cards is carried out twice:
with respect to the first category a:
Wt(A)＝MN(A1)*Pt(C)+MN(A2)*Pt(B)＝0*47.5％+0*31.25％＝0；
with respect to the second category B:
Wt(B)＝MN(B1)*Pt(C)+MN(B2)*Pt(B)＝(1/3)*47.5％+(1/2)*31.25％＝31.46％；
with respect to the third category C:
Wt(C)＝MN(C1)*Pt(C)+MN(C2)*Pt(B)＝(1/3)*47.5％+(1/6)*31.25％＝21.04％；
with respect to the fourth category D:
Wt(D)＝MN(D1)*Pt(C)+MN(D2)*Pt(B)＝(1/3)*47.5％+(1/3)*31.25％＝26.25％。
s43, card dealing recommendation is executed based on the occupation ratio, and cards in the category with the highest occupation ratio are recommended when the card dealing recommendation is executed;
as can be seen from the above, the card of player a is finally recommended to be the card in the second category B based on the recommendation method with the highest proportion rate.
In conclusion, the player can not only carry out the card-playing selection according to the card-playing type of the superior player in the game process, but also carry out the card-playing selection according to the card type to be acquired, thereby improving the flexibility of the card-playing of the player; meanwhile, according to the principle, the optimal recommendation is carried out in the whole recommendation card playing process by ensuring the balance of the card types owned by the players at present, so that the players can effectively deal with different fighting conditions in the whole game process, and the effect of improving the winning probability is achieved. Wherein, the upper player's interpretation is: taking player a as an example, the upper player should be player d.
Example 2
This embodiment is a further preferred embodiment of embodiment 1, the overall process and principle are the same as those of embodiment 1, and the difference is that: in this embodiment, a card-playing recommendation in a second predetermined game scene is also set, and the second predetermined game scene is a scene in which the player is attacked.
Specifically, in this embodiment, the following is presented:
after the current game scene is identified, if the current game scene is a second preset game scene, identifying whether cards acting on the second preset game scene exist in the cards currently owned by the player;
if yes, conducting card playing recommendation according to a second preset game scene;
otherwise, the game continues.
For example, the custom classification in embodiment 1 is: a first class A, a second class B, a third class C and a fourth class D; specifically, in the game battle, when one player uses any card in the first category a to another player, the other player can flash by any card in the second category B.
It is easy to explain that, in a game round, when any one of the players b/c/d uses the card in the first category a to the player a, the player a is in the scene of attack, and the card currently owned by the player a is recognized as:
first class a: 0 sheet; second class B: 2, placing the sheets;
the third category C: 1, 1 sheet; the fourth category D: 2 pieces of the Chinese herbal medicine.
Therefore, the cards currently owned by the player a contain second type B cards which can act on a second preset game scene, and at the moment, the player a is recommended to carry out the card playing operation of any card under the second type B.
While various steps have been illustrated and described as sequential processes, many of the steps may be performed in the alternative, in parallel, concurrently or in parallel. In addition, the order of the steps may be rearranged. Also, the process may be terminated when its operations are completed, but may have additional steps not included in the drawing. The processes may correspond to methods, functions, procedures, subroutines, subprograms, and the like.
Example 3
In an embodiment of the present invention, a card-out recommendation system in a card-game match-up game is further provided, and specifically, referring to fig. 2, a block diagram of the card-out recommendation system is shown, and as can be seen from the figure, the card-out recommendation system includes:
the game terminal comprises an identification module 10, a processing module and a processing module, wherein the identification module is used for identifying whether a current game scene is a preset game scene in the game terminal, and the preset game scene at least comprises a first preset game scene;
the obtaining module 20 is used for responding to the identification result of the identification module 10 and obtaining the types of the cards in the game and the remaining number of the cards in each type;
the calculating module 30 is used for calculating the category probability of the player for obtaining the next card according to the obtaining result of the obtaining module 20;
the preference and recommendation module 40 obtains cards currently owned by the player, and performs card-playing recommendation by combining the calculation result of the calculation module 30.
In this embodiment, the card-deal recommendation system is executed according to the card-deal recommendation method disclosed in embodiment 1 or embodiment 2 when executing card-deal recommendation.
Example 4
The embodiment of the invention also provides a game terminal which specifically comprises a storage and a processor;
the storage is stored with at least one executable code; at least one executable code is loaded and executed by the processor, and when loaded and executed, the at least one executable code implements the card-deal recommendation method disclosed in embodiment 1 or embodiment 2 above.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (10)

1. A card-out recommendation method in a card battle game is characterized by relating to a game terminal installed and operated with the card battle game, wherein the recommendation method is applied to the game terminal and comprises the following steps:
in the game terminal, identifying a current game scene;
when the current game scene is a first preset game scene, acquiring the category of cards in the current game and the remaining number of the cards in each category;
calculating the category probability of the player for obtaining the next card according to the remaining number of cards in each category;
obtaining cards currently owned by the player, and recommending card playing based on the category probability of the next card obtained by the player;
wherein:
the categories are categorized based on the current game's own rules and/or player customizations.
2. The method of claim 1, wherein the first predetermined game scenario is a scenario where the player is to play.
3. The method of claim 2, further comprising, after identifying the current game scenario:
when the current game scene is a second preset game scene, identifying whether cards acting on the second preset game scene exist in the cards currently owned by the player;
if yes, conducting card playing recommendation according to the second preset game scene;
otherwise, the game continues.
4. A method as claimed in claim 3, wherein the second predetermined game scenario is a scenario in which the player is under attack.
5. The method of claim 1, wherein the probability of the category to which the player has obtained the next card is calculated:
PtN/M; wherein t is any one of all categories, P is the probability that the next card acquired by the player belongs to the category t, N is the remaining number of cards in the category t, and M is the remaining total number of cards in all the categories.
6. The method of claim 1, wherein when the deal recommendation is made:
identifying categories of cards currently owned by the player and the number of cards in each category;
supplementing the counting cards to the player at least once, and determining the occupation ratio of each category in the calculation basis by taking the counting cards and the currently owned cards as the calculation basis;
and executing card-playing recommendation based on the high and low of the occupation ratio, and recommending cards in the category with the highest occupation ratio when executing the card-playing recommendation.
7. The method of claim 6, wherein the player is supplemented with the calculated cards by:
preferably, the probability of the category to which the player obtains the next card is ranked from high to low, and the category of the calculated card is determined based on the preferred ranking.
8. The method of claim 7, wherein when the number of times the player is replenished with the counting cards is N:
Wt＝M1*P1+……+MN*PN(ii) a Wherein:
t is any one of all categories, WtTo perform the total percentage of category t after N additions of cards, M1……MNFor performing N card additions a single occupation ratio, P, of category t1……PNThe category probability corresponding to each counting card when the N times of the supplement of the counting cards are executed;
n is any integer of 1 … … N;
MNQ/E; wherein:
MNthe single occupation ratio of the category t when the N-th card counting replenishment is executed is Q, and the number of cards under the category t in the calculation basis when the N-th card counting replenishment is executed is Q; e is the total card amount in the calculation basis when the Nth card counting supplement is executed.
9. A card-out recommendation system in a card-fighting game, comprising:
the game system comprises an identification module, a processing module and a processing module, wherein the identification module is used for identifying whether a current game scene is a preset game scene in a game terminal, and the preset game scene at least comprises a first preset game scene;
the acquisition module is used for responding to the identification result of the identification module and acquiring the category of the cards in the game and the remaining number of the cards in each category;
the calculating module is used for calculating the category probability of the player for obtaining the next card according to the obtaining result of the obtaining module;
and the preference and recommendation module is used for acquiring cards currently owned by the players and recommending the cards in a playing way by combining the calculation results of the calculation module.
10. A gaming terminal comprising a memory and a processor;
the storage is stored with at least one executable code; the at least one executable code is loaded and executed by a processor, and when loaded and executed implements the card deal recommendation method of any of claims 1-8.
CN202010540908.7A 2020-06-15 2020-06-15 Card playing recommendation method and system in card combat game and game terminal Active CN111729316B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010540908.7A CN111729316B (en) 2020-06-15 2020-06-15 Card playing recommendation method and system in card combat game and game terminal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010540908.7A CN111729316B (en) 2020-06-15 2020-06-15 Card playing recommendation method and system in card combat game and game terminal

Publications (2)

Publication Number Publication Date
CN111729316A true CN111729316A (en) 2020-10-02
CN111729316B CN111729316B (en) 2024-05-17

Family

ID=72649149

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010540908.7A Active CN111729316B (en) 2020-06-15 2020-06-15 Card playing recommendation method and system in card combat game and game terminal

Country Status (1)

Country Link
CN (1) CN111729316B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112295227A (en) * 2020-10-28 2021-02-02 北京字节跳动网络技术有限公司 Card game operation method and device, electronic equipment and storage medium
CN113274737A (en) * 2021-06-08 2021-08-20 网易（杭州）网络有限公司 Information recommendation method and device, computer equipment and medium

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101901304A (en) * 2010-08-05 2010-12-01 上海酷吧信息技术有限公司 Method for realizing intelligent algorithm for computer player in Doudizhu game
CN103877725A (en) * 2012-12-20 2014-06-25 腾讯科技（深圳）有限公司 Electronic chess and card data processing method and system
US20160284155A1 (en) * 2015-03-27 2016-09-29 Zynga Inc. Automated hand strength estimation for card games
CN106055339A (en) * 2016-06-08 2016-10-26 天津联众逸动科技发展有限公司 Method for determining card playing strategy of computer player in two-against-one game
CN110175619A (en) * 2018-11-27 2019-08-27 深圳市腾讯信息技术有限公司 Method, equipment and storage medium are determined based on the board group of playing a card of machine learning model
CN110457534A (en) * 2019-07-30 2019-11-15 深圳市腾讯网域计算机网络有限公司 A kind of data processing method based on artificial intelligence, device, terminal and medium
CN110478893A (en) * 2019-08-23 2019-11-22 网易（杭州）网络有限公司 Game events execute method and device

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101901304A (en) * 2010-08-05 2010-12-01 上海酷吧信息技术有限公司 Method for realizing intelligent algorithm for computer player in Doudizhu game
CN103877725A (en) * 2012-12-20 2014-06-25 腾讯科技（深圳）有限公司 Electronic chess and card data processing method and system
US20160284155A1 (en) * 2015-03-27 2016-09-29 Zynga Inc. Automated hand strength estimation for card games
US20180204409A1 (en) * 2015-03-27 2018-07-19 Zynga Inc. Automated hand strength estimation for card games
CN106055339A (en) * 2016-06-08 2016-10-26 天津联众逸动科技发展有限公司 Method for determining card playing strategy of computer player in two-against-one game
CN110175619A (en) * 2018-11-27 2019-08-27 深圳市腾讯信息技术有限公司 Method, equipment and storage medium are determined based on the board group of playing a card of machine learning model
CN110457534A (en) * 2019-07-30 2019-11-15 深圳市腾讯网域计算机网络有限公司 A kind of data processing method based on artificial intelligence, device, terminal and medium
CN110478893A (en) * 2019-08-23 2019-11-22 网易（杭州）网络有限公司 Game events execute method and device

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112295227A (en) * 2020-10-28 2021-02-02 北京字节跳动网络技术有限公司 Card game operation method and device, electronic equipment and storage medium
CN113274737A (en) * 2021-06-08 2021-08-20 网易（杭州）网络有限公司 Information recommendation method and device, computer equipment and medium
CN113274737B (en) * 2021-06-08 2024-02-02 网易（杭州）网络有限公司 Information recommendation method, device, computer equipment and medium

Also Published As

Publication number Publication date
CN111729316B (en) 2024-05-17

Similar Documents

Publication Publication Date Title
US7717783B2 (en) Computer-based, interactive, real-time card selection game
US6679777B2 (en) Playing an interactive real-time card selection game over a network
US11247128B2 (en) Method for adjusting the strength of turn-based game automatically
CN109806577B (en) Method, device, terminal and storage medium for showing card game
CN111729316A (en) Card-out recommendation method and system in card battle game and game terminal
KR20180117534A (en) Information processing device, game program, and information processing method
CN106075912A (en) A kind of method that online game is helped each other and network game system
CN111111196B (en) Online role playing game competition method and device and electronic equipment
KR101744359B1 (en) Game server, and computer-readable recording medium having recorded scenario controlling program therein
CN102646158A (en) Integral clearing method and system for Internet-based virtual adversarial game
CN112148393A (en) User team forming method based on social platform mini-game
CN112717425B (en) Information sending method, information display method, device, equipment and medium
CN114146401A (en) Mahjong intelligent decision method, device, storage medium and equipment
US20170136363A1 (en) Game system, and control method and storage medium used in same
JP7258711B2 (en) Programs, systems and methods for providing games
JP2007105071A (en) Network game system for executing network game, and server device
CN112138389A (en) Game role recommendation display method, system and equipment
JP2010200975A (en) Game system, game management method, and game management program
CN113485924B (en) Game test method, device, equipment and storage medium
TWI250421B (en) Method of playing chess with an artificial intelligent device
KR101996423B1 (en) Device and method for providing personalized gamification component
JP7149308B2 (en) SYSTEM, METHOD AND PROGRAM FOR PROVIDING A GAME
US20090045575A1 (en) Poker game method and device
US11495094B1 (en) Entertainment system
CN116688523A (en) Card interaction method and device, computer equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant