Thursday Morning Talk

Abstract:Theories of learning from multimodal sources (e.g., combinations of text and pictures, aka multimedia) posit that in order to effectively learn from multimedia, students need to select information from text

Abstract: Collective dynamics play a crucial role in everyday decision-making. Whether social influence promotes the spread of accurate information, and ultimately results in collective intelligence, or leads to false information

Abstract: I will present our current research involving the Robofish. I will put a special focus on our latest research paper that found live fish to be able to anticipate

From writing essays to evaluating potential hires, machines are doing a lot these days. In all spheres of life, it seems that machines are being delegated more and more decisions.

More details to follow. Photo by DeepMind on Unsplash This talk will take place in person at SCIoI.  

Abstract: As many of us know by now, Deep Learning has enabled tackling very challenging problems and applications that were previously almost impossible to solve with machine learning. However, for

Abstract: The BUA-funded experimental knowledge transfer project CollActive Materials, a collaboration between the Clusters of Excellence Science of Intelligence and Matters of Activity, encourages speculation on what the future has

Abstract: The contents of this presentation will be twofold. In the first part the Centre for Robotics of the Queensland University of Technology (QUT) and its research directions and facilities

Abstract: The aim of SCIoI’s P10 is to investigate how anticipation and prediction shapes social interactions among live and artificial agents using for example the Robofish system. We will outline

Abstract: Lack of data and annotations has been the showstopper for machine learning projects when I started my PhD and 15 years later it still is. In my talk, I

Abstract: A central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret

Abstract:  In groups of agents learning how to solve a common task, interaction and knowledge transfer between agents is important and can vary depending on network topology. Heterogeneity is one