US 10,881,964 B1Granted

Automated detection of emergent behaviors in interactive agents of an interactive environment

AssigneeElectronic Arts Inc.

InventorThomas Bradley Dills

Life of this patent

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Abstract

Various aspects of the subject technology relate to systems, methods, and machine-readable media for automated detection of emergent behaviors in interactive agents of an interactive environment. The disclosed system represents an artificial intelligence based entity that utilizes a trained machine-learning-based clustering algorithm to group users together based on similarities in behavior. The clusters are processed based on a determination of the type of activity of the clustered users. In order to identify new categories of behavior and to label those new categories, a separate cluster analysis is performed using interaction data obtained at a subsequent time. The additional cluster analysis determines any change in behavior between the clustered sets and/or change in the number of users in a cluster. The identification of emergent user behavior enables the subject system to treat users differently based on their in-game behavior and to adapt in near real-time to changes in their behavior.

Claims13

Dependent claims

A computer-implemented method, comprising:

obtaining first interaction data of a participant device in a multiuser session of an interactive environment based on interactions between an interactive agent associated with a user and the interactive environment;
obtaining second interaction data of the participant device based on subsequent interactions between the interactive agent and the interactive environment;
analyzing the first interaction data and the second interaction data with a machine-learning-based cluster analysis model comprising an output of an artificial neural network;
determining a behavior signature of each of a plurality of interactive agents based on the analyzed first and second interaction data;
detecting an emergent behavior associated with a cluster comprised of a subset of interactive agents of the plurality of interactive agents with similar behavior signatures, the detecting comprising:
comparing a first metric value of the interactive agent from the first interaction data to a second metric value of the interactive agent from the second interaction data;
determining a difference between the first metric value and the second metric value, wherein the first metric value corresponds to a first cluster of the plurality of clusters and the second metric value corresponds to a second cluster of the plurality of clusters, the second cluster being different from the first cluster;
and
determining, from the first and second interaction data corresponding to a same cluster, that a behavior signature of the interactive agent corresponds to the emergent behavior based on the determined difference and metric values of other interactive agents, the other interactive agents having similar attributes as that of the interactive agent;
and
adjusting a status of a user corresponding to an interactive agent associated with the detected emergent behavior.

8 more elements

A non-transitory computer readable storage medium is provided including instructions that, when executed by a processor, cause the processor to perform a method, the method comprising:

obtaining first interaction data of a participant device in a multiuser session of an interactive environment based on interactions between an interactive agent associated with a user and an interactive environment;
obtaining second interaction data of the participant device based on subsequent interactions between the interactive agent and the interactive environment;
analyzing the first interaction data and the second interaction data with a machine-learning-based cluster analysis model comprising an output of an artificial neural network;
determining a behavior signature of each of a plurality of interactive agents based on the analyzed first and second interaction data;
detecting an emergent behavior associated with a cluster comprised of a subset of interactive agents of the plurality of interactive agents with similar behavior signatures the detecting comprising:
comparing a first metric value of the interactive agent from the first interaction data to a second metric value of the interactive agent from the second interaction data;
determining a difference between the first metric value and the second metric value, wherein the first metric value corresponds to a first cluster of the plurality of clusters and the second metric value corresponds to a second cluster of the plurality of clusters, the second cluster being different from the first cluster;
and
determining, from the first and second interaction data corresponding to a same cluster, that a behavior signature of the interactive agent corresponds to the emergent behavior based on the determined difference and metric values of other interactive agents, the other interactive agents having similar attributes as that of the interactive agent;
and
adjusting a status of a user corresponding to an interactive agent associated with the detected emergent behavior.

8 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/130,854Filed 13 Sep 2018
Granted: 5 Jan 2021
Term ends: Not estimatedThe source records don’t support an estimate.

Classification20 codes

A63F 13/67
Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or…:…
A63F 13/35
Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection…: details…
A63F 13/46
Controlling the progress of the video game: computing the game score
A63F 13/75
Game security or game management aspects: enforcing rules, e.g. detecting foul play or generating lists of cheating players