MULTIPLAYER VIDEO GAME MATCHMAKING OPTIMIZATION

• US 20170259178A1
• Filed: 03/08/2016
• Published: 09/14/2017
• Est. Priority Date: 03/08/2016
• Status: Active Grant

• Current Assignee: Electronic Arts Incorporated
• Original Assignee: Electronic Arts Incorporated
• Inventors: Aghdaie, Navid, Kolen, John, Mattar, Mohamed Marwan, Sardari, Mohsen, Xue, Su, Zaman, Kazi Atif-Uz
• Granted Patent: US 9,993,735 B2
• Time in Patent Office: Days
• CPC Class Codes: A63F 13/73 Authorising game programs or game devices, e.g. checking authenticity
• CPC Class Codes: A63F 13/75 Enforcing rules, e.g. detecting foul play or generating lists of cheating players
• CPC Class Codes: A63F 13/795 for finding other players; for building a team; for providing a buddy list
• CPC Class Codes: A63F 2300/5566 by matching opponents or finding partners to build a team, e.g. by skill level, geographical area, background, play style

Abstract

Embodiments of systems presented herein may identify users to include in a match plan. A parameter model may be generated to predict the retention time of a set of users. A queue of potential users, a set of teammates, and/or opponents may be selected from a queue of waiting users. User information for the set of teammates and/or opponents may be provided to the parameter model to generate a predicted retention time. The set of teammates and/or opponents may be approved if the predicted retention time meets a predetermined threshold. Advantageously, by creating a match plan based on retention rates, the engagement and/or retention level for a number of users may be improved compared to existing multiplayer matching systems.

Claims

1. A computer-implemented method comprising:

as implemented by an interactive computing system configured with specific computer-executable instructions,

selecting a plurality of users from a queue of users waiting to play an instance of a video game, wherein at least a first portion of the instance of the video game executes on a user computing device of at least one user from the queue of users and a second portion of the instance of the video game executes on the interactive computing system;

for each user from the plurality of users, accessing a set of input data associated with the corresponding user, the set of input data comprising user interaction data associated with the corresponding user'"'"'s interaction with the video game;

determining a predicted retention rate for each user from the plurality of users based at least in part on the set of input data for each user from the plurality of users, the predicted retention rate indicating an amount of time each user from the plurality of users will play the video game;

determining whether the predicted retention rates of the plurality of users satisfy a retention threshold; and

in response to the predicted retention rates satisfying the retention threshold, initiating the instance of the video game with the plurality of users as players of the instance of the video game.

2. The computer-implemented method of claim 1, wherein, in response to the predicted retention rates failing to satisfy the retention threshold, the computer-implemented method further comprises selecting a new plurality of users from the queue of users waiting to play the instance of the video game.

3. The computer-implemented method of claim 2, wherein at least one user from the plurality of users is included with the new plurality of users.

4. The computer-implemented method of claim 1, wherein the plurality of users comprises a subset of users included in the queue of users, and wherein the plurality of users is selected based on one or more selection criteria.

5. The computer-implemented method of claim 4, wherein the selection criteria includes one or more of the following:

length of time of a user in the queue;

geographic location of the user;

inclusion on a blacklist of the user;

geographic distance from a host server of the interactive computing system that hosts the second portion of the instance of the video game;

or network distance from the host server.

6. The computer-implemented method of claim 1, wherein determining the predicted retention rate for each user from the plurality of users comprises:

providing, for each user from the plurality of users, the set of input data to a parameter function, the parameter function generated based at least in part on a machine learning algorithm; and

determining the predicted retention rate for each user from the plurality of users based at least in part on an output of the parameter function.

7. The computer-implemented method of claim 6, further comprising generating the parameter function by at least:

accessing training input data, the training input data associated with a second plurality of users who play the video game;

accessing a set of output data for the second plurality of users, the output data associated with a retention rate for the second plurality of users; and

using the machine learning algorithm to determine the parameter function based at least in part on the set of input data and the set of output data.

8. The computer-implemented method of claim 6, further comprising associating a penalty with the parameter function based at least in part on one or more of the following:

a number of variables included in the parameter function;

a complexity of a mathematical algorithm associated with the parameter function;

or an accuracy of an output of the parameter function compared to the output data.

9. The computer-implemented method of claim 6, further comprising selecting the parameter function from a plurality of parameter functions based at least in part on a penalty value associated with at least some of the parameter functions from the plurality of parameter functions.

10. The computer-implemented method of claim 1, further comprising:

receiving an indication that a first user and a second user from the plurality of users desire to play the same instance of the video game; and

in response to the predicted retention rate failing to satisfy the retention threshold, replacing at least some of the plurality of users with different users while maintaining the first user and the second user within the plurality of users.

11. The computer-implemented method of claim 1, wherein the user interaction data includes one or more of the following:

a play style;

a skill level;

a character selection history;

or a role history.

12. The computer-implemented method of claim 1, further comprising associating a particular set of user interaction data with a user from the plurality of users in response to determining that the user is associated with less than a threshold amount interaction history with the video game.

13. A system comprising:

an electronic data store configured to store user interaction data for users of a video game;

a hardware processor in communication with the electronic data store, the hardware processor configured to execute specific computer-executable instructions to at least;

select a set of users from a queue of users waiting to play a video game, wherein at least a first portion of the video game is hosted on a user computing device of at least one user from the queue of users and a second portion of the video game is hosted by a server system;

generate a match plan based on the set of users, wherein each match plan comprises a first team of users from the set of users and a second team of users from the set of users;

for each user from the set of users, access a set of user interaction data associated with the user;

determine an engagement score for the match plan based at least in part on the set of user interaction data associated with each of the users from the set of users;

determine whether the engagement score satisfies an engagement score threshold; and

in response to determining that the engagement score satisfies the engagement score threshold, initiate an instance of the video game using the match plan.

14. The system of claim 13, wherein the match plan is one of a plurality of match plans, and wherein the hardware processor is further configured to execute specific computer-executable instructions to at least select the match plan from the plurality of match plans based at least in part on each match plans engagement score.

15. The system of claim 13, wherein, in response to determining that the engagement score does not satisfy the engagement score threshold, the hardware processor is further configured to execute specific computer-executable instructions to at least substitute at least one user from the set of users with another user from the queue of users.

16. The system of claim 15, wherein at least a first user and a second user are designated as a user pair, and wherein substituting at least one user from the set of users with another user from the queue of users includes maintaining the user pair.

17. The system of claim 13, wherein the engagement score threshold varies based at least in part on the number of users included in the queue of users.

18. A non-transitory computer-readable storage medium storing computer executable instructions that, when executed by one or more computing devices, configure the one or more computing devices to perform operations comprising:

selecting a plurality of users from a queue of users waiting to play an instance of a video game to form a match plan for playing an instance of the video game;

for each user from the plurality of users, accessing a set of user interaction data associated with the user'"'"'s interaction with the video game;

determining a predicted retention rate the match plan based at least in part on the set of user interaction data for each of the plurality of users, the predicted retention rate corresponding to a probability that a particular number of users from the plurality of users cease to play the video game;

determining whether the predicted retention rate satisfies a retention threshold; and

in response to the predicted retention rate satisfying the retention threshold, selecting the match plan to play the instance of the video game.

19. The computer-readable, non-transitory storage medium of claim 18, wherein determining the predicted retention rate comprises:

providing the set of user interaction data for each user of the match plan to a parameter function generated based at least in part on a machine learning algorithm; and

determining the predicted retention rate for the match plan based at least in part on an output of the parameter function.

20. The computer-readable, non-transitory storage medium of claim 19, wherein the output of the parameter function comprises the predicted retention rate for the match plan and an identity of a number of users associated with retention rates that do not satisfy a second retention threshold, wherein the retention threshold and the second retention threshold differ.