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Using playstyle patterns to generate virtual representations of game players

A game mode, game technology, applied in indoor games, video games, based on specific mathematical modes, etc., can solve problems such as unrealistic gameplay

Pending Publication Date: 2020-10-09
NVIDIA CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, when users play against these bots, the gameplay is often unrealistic

Method used

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  • Using playstyle patterns to generate virtual representations of game players
  • Using playstyle patterns to generate virtual representations of game players
  • Using playstyle patterns to generate virtual representations of game players

Examples

Experimental program
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Embodiment Construction

[0018] Systems and methods related to controlling a virtual representation ("bot") of a user using learned play style patterns are disclosed. For example, in contrast to conventional systems, one or more machine learning models are used to learn the user's play style patterns, and the instantiation of the bot is controlled according to the play style patterns. As a result, not only is the bot more human-like than existing bots, but the user is able to compete with other players (e.g., players the user has lost to in the past, players who are better than the user, players the user may face in real time in the future, Virtual representations of specific well-known players, etc.) or virtual representations of player classes (e.g., players with a certain experience level, players from a specific geographic location, etc.) without regard to the availability of specific players, or without constant search Game sessions with a specific category of players (even if the player is found...

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PUM

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Abstract

The invention discloses using playstyle patterns to generate virtual representations of game players. In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (''robot(bots)'') of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, orof categories of users, according to the learned playstyle patterns.

Description

Background technique [0001] With the proliferation of online multiplayer video games, and games becoming more competitive, users are spending more and more time training to improve their in-game skills. To accomplish this, users often try to play against players who are better or higher ranked than themselves. For example, when a user loses a game session with a particular player, the user may wish to recreate the game session by playing against the same player. However, a player from a previous game session may not be available or willing to play, especially if that player is from a competitor's professional team. Additionally, the player may play another game session differently (eg, the player may be more cautious than the original game session, or may take the game less seriously), further reducing the chances that the user will be able to duplicate the game session. Although difficult to replicate for a single player, replication of the original game session becomes mor...

Claims

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Application Information

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IPC IPC(8): A63F13/55A63F13/67A63F13/79A63F13/795A63F13/825G06N20/00
CPCA63F13/55A63F13/825A63F13/79A63F13/795A63F13/67G06N20/00A63F13/56A63F13/798A63F13/355G06N3/006G06N3/08G06N3/045G06N3/088G06N7/00A63F13/49A63F2300/558A63F2300/535A63F13/60A63F2300/55A63F13/497A63F2300/6027A63F2300/5546A63F2300/208
Inventor A·费尔B·伯克P·V·N·H·普拉萨德A·拉尔瓦尼
Owner NVIDIA CORP
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