Abstract: In various implementations, a device surveys a scene and presents, within the scene, a extended reality (XR) environment including one or more assets that evolve over time (e.g., change location or age). Modeling such an XR environment at various timescales can be computationally intensive, particularly when modeling the XR environment over larger timescales. Accordingly, in various implementations, different models are used to determine the environment state of the XR environment when presenting the XR environment at different timescales.

Abstract: In various implementations, a device surveys a scene and presents, within the scene, a extended reality (XR) environment including one or more assets that evolve over time (e.g., change location or age). Modeling such an XR environment at various timescales can be computationally intensive, particularly when modeling the XR environment over larger timescales. Accordingly, in various implementations, different models are used to determine the environment state of the XR environment when presenting the XR environment at different timescales.

Abstract: In various implementations, a device surveys a scene and presents, within the scene, a extended reality (XR) environment including one or more assets that evolve over time (e.g., change location or age). Modeling such an XR environment at various timescales can be computationally intensive, particularly when modeling the XR environment over larger timescales. Accordingly, in various implementations, different models are used to determine the environment state of the XR environment when presenting the XR environment at different timescales.

Abstract: In one implementation, a method of generating an environment state is performed by a device including one or more processors and non-transitory memory. The method includes obtaining a first environment state of an environment, wherein the first environment state indicates the inclusion in the environment of a first asset associated with a first timescale value and a second asset associated with a second timescale value, wherein the first environment state further indicates that the first asset has a first state of the first asset and the second asset has a first state of the second asset. The method includes determining a second state of the first asset and the second asset based on the first and second timescale value. The method includes determining a second environment state that indicates that the first asset has the second state and the second asset has the second state.

Abstract: In various implementations, a device surveys a scene and presents, within the scene, a extended reality (XR) environment including one or more assets that evolve over time (e.g., change location or age). Modeling such an XR environment at various timescales can be computationally intensive, particularly when modeling the XR environment over larger timescales. Accordingly, in various implementations, different models are used to determine the environment state of the XR environment when presenting the XR environment at different timescales.