Abstract: Methods and systems for sound propagation and perception for autonomous agents in dynamic environments are described. Adaptive discretization of continuous sound signals allows one to obtain a minimal, yet sufficient sound packet representation (SPR) for human-like perception, and a hierarchical clustering scheme to facilitate approximate perception. Planar sound propagation of discretized sound signals exhibit acoustic properties such as attenuation, reflection, refraction, and diffraction, as well as multiple convoluted sound signals. Agent-based sound perceptions using hierarchical clustering analysis that accommodates natural sound degradation due to audio distortion facilitate approximate human-like perception.

Abstract: Methods and systems for sound propagation and perception for autonomous agents in dynamic environments are described. Adaptive discretization of continuous sound signals allows one to obtain a minimal, yet sufficient sound packet representation (SPR) for human-like perception, and a hierarchical clustering scheme to facilitate approximate perception. Planar sound propagation of discretized sound signals exhibit acoustic properties such as attenuation, reflection, refraction, and diffraction, as well as multiple convoluted sound signals. Agent-based sound perceptions using hierarchical clustering analysis that accommodates natural sound degradation due to audio distortion facilitate approximate human-like perception.

Abstract: Methods and systems for sound propagation and perception for autonomous agents in dynamic environments are described. Adaptive discretization of continuous sound signals allows one to obtain a minimal, yet sufficient sound packet representation (SPR) for human-like perception, and a hierarchical clustering scheme to facilitate approximate perception. Planar sound propagation of discretized sound signals exhibit acoustic properties such as attenuation, reflection, refraction, and diffraction, as well as multiple convoluted sound signals. Agent-based sound perceptions using hierarchical clustering analysis that accommodates natural sound degradation due to audio distortion facilitate approximate human-like perception.

Abstract: Methods and systems for sound propagation and perception for autonomous agents in dynamic environments are described. Adaptive discretization of continuous sound signals allows one to obtain a minimal, yet sufficient sound packet representation (SPR) for human-like perception, and a hierarchical clustering scheme to facilitate approximate perception. Planar sound propagation of discretized sound signals exhibit acoustic properties such as attenuation, reflection, refraction, and diffraction, as well as multiple convoluted sound signals. Agent-based sound perceptions using hierarchical clustering analysis that accommodates natural sound degradation due to audio distortion facilitate approximate human-like perception.

Abstract: This invention relates to methods and systems for simulation and representation of the behavior of individuals in a high-density autonomous crowd in response to a changing dynamic environment.