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

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

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

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. I show that through decentralized voting algorithms, swarms of minimalistic robots can make best-of-n decisions. In my research, I show that using a biologically-inspired voting

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 of learning. But what is the relationship between the two? How should the two interact? Do they even have to? What could be a common

Abstract:  This talk will be targeting junior postdocs and phd at their final stages. It will be a short and brief introduction to the major options for grants (those aiming at the stars or smaller ones). Julten will offer some quick tips on the application process. She will also share her own experience in applying

Abstract: The capabilities of AI systems are improving rapidly, and these systems are being deployed in increasingly complex and high-stakes contexts, from self-driving cars to the detection of medical conditions. As the importance of AI grows, so too does the need for robust evaluation. If we want to determine the extent to which systems are