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: Learning is a central concept in many scientific disciplines. Communication about research on learning is, however, hampered by the fact that different researchers define learning in different ways. In
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: The brain is a complex dynamical system with processes operating on different spatial scales. At the macroscopic end one observes global dynamical phenomena, which are called „brain states“ and
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
Many claims have been made that machine intelligence could make humans superfluous in the near future. Today this claim is largely seen as overstated, but it is still important to
Abstract: We can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference, or an assembly of biological components not built for achieving statistical optimality. The
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
Abstract: Swarm robotics is a promising approach to the coordination of large groups of robots. Traditionally, the design of collective behaviors for robot swarms has been an iterative manual process:
Abstract: Unsupervised learning is experiencing a renaissance. Driven by an abundance of unlabelled data and the advent of deep generative models, machines are now able to synthesise complex images, videos
Marchstr. 23 – MAR 5-2
10587 Berlin
Email: info@scioi.de
Tel: +49 30 314 77344
