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
Abstract: 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
Lars Lewejohann, Freie Universität Berlin, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R) Mice, like all other living creatures, have adapted to
Abstract: I investigate how large groups of simple robots can reach a consensus with decentralized minimalistic algorithms. Simple robots can be useful in nanorobotics and in scenarios with low-cost requirements.
Abstract: Biological intelligent systems manifest their intelligence in physical interactions with other agents and with their environment. Such interactions require embodiment. Intelligence, both artificial and biological, also requires some kind
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