When a first input is performed in a predetermined scene, options including elements available in a predetermined game are presented. An element to be used in the predetermined game is determined on the basis of an operation input by a user. In response to a second input, the predetermined game using the determined element is executed. Meanwhile, at a predetermined timing before the predetermined game is started, an element to be used in the predetermined game is automatically determined. When a third input is performed in the predetermined scene, the predetermined game is executed using the automatically determined element. After the predetermined game is ended, a first reward is given to the user if the element used in the predetermined game is the element determined on the basis of the operation input by the user, and a second reward is given if the element is the automatically determined element.

Provided are a method, program, system, and server for verifying a game program. Provided is a method executed by a system for verifying a game program for executing a collaborative game with another player by using a deck including a plurality of game media, wherein a deck set includes a plurality of decks, a deck combination is a combination of decks used to execute one collaborative game, and a deck combination set includes a plurality of deck combinations. The method includes: executing the game program in a plurality of virtual instances generated in order to virtualize a user terminal for playing the game or the software environment of the user terminal; executing the collaborative game in a first mode until a predetermined verification coverage is reached; and executing the collaborative game in a second mode after the predetermined verification coverage has been reached.

Provided are a method, program, system, and server for verifying a game program. Provided is a method executed by a system for verifying a game program for executing a collaborative game with another player by using a deck including a plurality of game media, wherein a deck set includes a plurality of decks, a deck combination is a combination of decks used to execute one collaborative game, and a deck combination set includes a plurality of deck combinations. The method includes: executing the game program in a plurality of virtual instances generated in order to virtualize a user terminal for playing the game or the software environment of the user terminal; executing the collaborative game in a first mode until a predetermined verification coverage is reached; and executing the collaborative game in a second mode after the predetermined verification coverage has been reached.

An improved virtual environment creation and testing process can be achieved by a combination of spatial partitioning and reverse tree generation. The reverse tree may be representative of the virtual environment and may be generated starting from a smallest portion or zone of the virtual environment (represented as a leaf node) and expanding up towards a root node representative of the entire virtual environment. Advantageously, the system can add new zones to the virtual environment and representative tree data structure that are external to the existing virtual environment without generating a new tree data structure. Thus, the computing resources utilized by the system disclosed herein may be significantly reduced compared to existing processes while improving the flexibility of the spatial partitioning and tree generation process thereby enabling spatial partitioning to be performed in real or near real time as a developer authors the virtual environment.

A method of generating audio assets, comprising the steps of: receiving a plurality of input audio assets, converting each input audio asset into an input graphical representation, generating an input multi-channel image by stacking each input graphical representation in a separate channel of the image, feeding the input multi-channel image into a generative model to train the generative model and generate one or more output multi-channel images, each output multi-channel image comprising an output graphical representation, extracting the output graphical representations from each output multi-channel image and converting each output graphical representation into an output audio asset.

A method of generating audio assets, comprising the steps of: receiving a plurality of input audio assets, converting each input audio asset into an input graphical representation, generating an input multi-channel image by stacking each input graphical representation in a separate channel of the image, feeding the input multi-channel image into a generative model to train the generative model and generate one or more output multi-channel images, each output multi-channel image comprising an output graphical representation, extracting the output graphical representations from each output multi-channel image and converting each output graphical representation into an output audio asset.

A method of generating audio assets, comprising the steps of: receiving an input multi-layered audio asset comprising a plurality of audio layers, generating an input multi-channel image, wherein each channel of the input multi-channel image comprises an input image representative of one of the audio layers, training a generative model on the input multi-channel image and implementing the trained generative model to generate an output multi-channel image, wherein each channel of the output multi-channel image comprises an output image representative of an output audio layer, and generating an output multi-layered audio asset based on a combination of output audio layers derived from the output images.

A method of generating audio assets, comprising the steps of: receiving an input multi-layered audio asset comprising a plurality of audio layers, generating an input multi-channel image, wherein each channel of the input multi-channel image comprises an input image representative of one of the audio layers, training a generative model on the input multi-channel image and implementing the trained generative model to generate an output multi-channel image, wherein each channel of the output multi-channel image comprises an output image representative of an output audio layer, and generating an output multi-layered audio asset based on a combination of output audio layers derived from the output images.

An information processing device for executing a game in which a new quest can be executed based on an update that adds the new quest to an existing quest, and a new content becomes usable based on an update that adds the new content to an existing content, includes: a decision means for deciding a used content to be used in one quest, which is the existing quest, from contents associated with a player; an execution means for executing the one quest based on a parameter of the used content; and a granting means for granting a reward to the player in response to satisfying a clearance condition in the executed one quest. The granting means prioritizes the reward when a usable time of the used content is earlier than a specific time stored in association with the one quest.

An information processing device for executing a game in which a new quest can be executed based on an update that adds the new quest to an existing quest, and a new content becomes usable based on an update that adds the new content to an existing content, includes: a decision means for deciding a used content to be used in one quest, which is the existing quest, from contents associated with a player; an execution means for executing the one quest based on a parameter of the used content; and a granting means for granting a reward to the player in response to satisfying a clearance condition in the executed one quest. The granting means prioritizes the reward when a usable time of the used content is earlier than a specific time stored in association with the one quest.