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Distinguished Speaker Series

Jan De Houwer (Ghent University), “Learning in Individual Organisms, Genes, Machines, and Groups: A New Way of Defining and Relating Learning in Different Systems”

MAR 2.057

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 this talk, we introduce the extended functional definition of learning that can be used across scientific disciplines. We provide examples of how the definition can

Thursday Morning Talk

David Bierbach (Science of Intelligence), “Anticipation in social interactions among live and artificial agents”

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 our research showing the sophisticated anticipation abilities of live fish, as well as how we integrated prediction and anticipation into Robofish’s social interaction behaviors. We

PI Lecture

Klaus Obermayer (Science of Intelligence), “Computational Models of Electric Field Effects and Optimal Control of Neurons and Neural Populations”

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 which are often acompanied by oscillations in different frequency bands or by specific functional connectivity patterns between populations of neuron. A common hypothesis states, that

Thursday Morning Talk

Robert Lange and Luis Gomez (Science of Intelligence), “Quantifying and modelling collective behavior across ecological contexts”

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 such collective concept, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as

Distinguished Speaker Series

Peter Neri (Laboratoire des Systèmes Perceptifs, CNRS, Paris), “The unreasonable recalcitrance of human vision to theoretical domestication”

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 former approach is attractive thanks to its elegance and potentially wide applicability, however the basic facts of human pattern vision do not support it. Instead,

Thursday Morning Talk

Dustin Lehmann, Fritz Francisco, Jorg Raisch, Pawel Romanczuk (Science of Intelligence), “Dynamical adaptation and learning: Knowledge transfer and cooperative learning in groups of heterogeneous agents”

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 of the key principles that influences the type and quality of interaction between learning agents. Different learning strategies and behaviors can be a driving factor

Thursday Morning Talk

David Garzón Ramos (Université Libre de Bruxelles), “Automatic design of robot swarms: context and experiments”

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: a human designer manually refines the control software of the individual robots until the desired collective behavior emerges. In this talk, I discuss automatic design

Distinguished Speaker Series

Ingmar Posner (University of Oxford), “Learning to Perceive and to Act – Disentangling Tales from (Structured) Latent Space”

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 and sounds. In robotics, one of the most promising features of these models - the ability to learn structured latent spaces - is gradually gaining

Thursday Morning Talk

Scott Robins (Bonn University), “What Machines Shouldn’t Do”

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 decisions. Some of these machines are being delegated decisions that could have significant impact on human lives.Examples of such machines which have caused such impact

Lars Lewejohann (Science of Intelligence), “What’s on a mouse’s mind? Behavioral measures to understand experiences and needs of an animal”

MAR 2.057

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 specific living conditions in the course of evolution. From a human point of view, the behavior of animals is therefore not always easy to understand.