Flock Logic is an art and engineering project that explores how the feedback laws used to model flocking translate when applied by a group of dancers. The artistic goal is to create tools for choreography by leveraging dynamics of multiagent systems with designed feedback and interaction. The engineering goal is to develop insights and design principles for multi-agent systems, such as human crowds, animal groups and mobile robotic networks, by examining the connections between what individual dancers do and what emerges at the level of the group. We describe our methods to create dance and investigate collective motion. To illustrate, we analyze the overhead video of an experiment in which thirteen dancers moved according to simple rules of cohesion and repulsion in response to the relative position and motion of their neighbors. Importantly, because we have prescribed the interaction protocol, we can estimate from the tracked trajectories the time-varying graph that defines who is responding to whom as time evolves. We compute time-varying status of nodes in the graph and infer conditions under which certain individuals emerge as leaders.

Abstract. Flock Logic was developed as an art and engineering project to explore how the feedback laws used to model flocking translate when applied by dancers. The artistic goal was to create choreographic tools that leverage multi-agent system dynamics with designed feedback and interaction. The engineering goal was to provide insights and design principles for multi-agent systems, such as human crowds, animal groups and robotic networks, by examining what individual dancers do and what emerges at the group level. We describe our methods to create dance and investigate collective motion. We analyze video of an experiment in which dancers moved according to simple rules of cohesion and repulsion with their neighbors. Using the prescribed interaction protocol and tracked trajectories, we estimate the time-varying graph that defines who is responding to whom. We compute status of nodes in the graph and show the emergence of leaders. We discuss results and further directions.

Auralization is an invaluable decision-making tool for the acoustical design of restaurants and other public gathering spaces, and accurate modeling and calibration of sound sources is critical to achieving perceptually plausible soundscapes of such spaces. Unlike auralizations of performing arts venues, auralizations of restaurants and public gathering spaces afford owners, architects, and consultants the opportunity to directly experience how difficult (or easy) it is to communicate with others when immersed in the soundscape. Also unlike auralizations of performing arts venues, a realistic auralization of a restaurant or public gathering space must account for the Lombard Effect when calibrating source levels of occupant and activity noise. In this presentation, we will briefly review the history and recent improvements of Acentech’s 3DListening studio in Cambridge, MA, including Lombard Effect modeling. Three recent case studies will be used to illustrate the unique role of auralization in the architectural design process, including a restaurant, a college pub located underneath residences, and a multi-level collaborative, interdisciplinary work space at an independent school.

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Computer modeling and auralization have proven their value in the acoustical design of performance venues. However, achieving and evaluating parametric accuracy and perceptual plausibility continues to be a challenge. Advances in our measurement techniques have given us new opportunities to test our models against reality in several recently completed spaces. Impulse responses were collected from the built spaces using a B-format (multichannel) microphone, and these were analyzed in terms of numerical acoustical parameters, and for directionality and timing of reflected sound arrival. These multichannel impulse responses were also convolved with speech and music, and listening comparisons were made with the same speech and music convolved with simulated impulse responses. This session will present the results of these tests and lessons learned regarding strengths and limitations of these techniques.