Many kinds of interactions among individuals construct collective animal behavior, but how to apply this multiplicity of interactions is often unclear when constructing models. We propose multiplicity of interaction in a simple model constructed from three factors: asynchronous updating, learning site patterns, and agent anticipation. We found that the first two contribute to an efficient searc...

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task ...

Decentralized control for multirobot systems is difficult to design by hand because the behavioral rules for individual robots cannot, in general, be derived from a desired collective behavior. System designers have therefore resorted to evolutionary computation as a means to heuristically synthesize self-organized behaviors for robot collectives. Evolutionary computation is typically applied b...

My group and I feel tremendously honored to be recognized with the 2016 Early Career Life Scientist Award from the American Society for Cell Biology. In this essay I share the scientific questions that my lab has been excitedly pursuing since starting in August 2009 and the leadership behaviors we have adopted that enable our collective scientific productivity.

Collective behavior refers to how individuals behave when they are exposed in a social network environment. In this article, we examine how we can predict online behaviors of users in a network, given the behavior information of some actors in the network. Many social media tasks can be connected to the problem of collective behavior prediction. Since connections in a social network represent v...

What are the management practices that foster collective learning within an organization? A lack of integration between the organizational learning and human resource management literatures means that this important question remains unanswered. Based on a study of 961 employees in 72 worldwide departments of a global pharmaceuticals company, we map the contextual dimensions of discipline, stret...

In this work, a Multi-agent Reinforcement Learning framework is used to get plausible simulations of pedestrians groups. In our framework, each virtual agent learns individually and independently to control its velocity inside a virtual environment. The case of study consists on the simulation of the crossing of two groups of embodied virtual agents inside a narrow corridor. This scenario permi...

Several works have been proposed for both collective and individual trajectory behavior discovery, as flocks, outliers, avoidance, chasing, etc. In this paper we are especially interested in abnormal behaviors of individual trajectories of drivers, and present an algorithm for finding anomalous movements and categorizing levels of driving behavior. Experiments with real trajectory data show tha...

The manner by which the organization and behaviors of cells arise from the activities of their constituent molecules remains poorly understood. Approaches from the physical sciences for studying collective properties may help with this difficult problem, but they must be adapted to account for the specific attributes of biological molecules.