PI Lecture

Pascal Klink (TU Darmstadt): Self-paced Reinforcement Learning

MAR23 4.064 Marchstraße 23, Berlin, Germany

Thursday Morning Lectures Abstract: Generalization and adaptation of learned skills to novel situations is a core requirement for intelligent autonomous robots. Although contextual reinforcement learning provides a principled framework for learning and generalization of behaviors across related tasks, it generally relies on uninformed sampling of environments from an unknown, uncontrolled context distribution, thus missing the

PI Lecture

Martin Rolfs (SCIoI): The impact of visual actions on human vision

On ZOOM (Contact us for Link)

PI Lecture on Zoom The impact of visual actions on human vision More than 10,000 times every waking hour, we use rapid movements of our eyes, head and body to reorient our gaze. These visual actions allow us to see every aspect of the visual world at the highest resolution. It seems likely — in

PI Lecture

Rebecca Lazarides (SCIoI): The role of teaching and instruction for human learning processes

On ZOOM (Contact us for Link)

Abstract: Learning - here defined as knowledge acquisition and behavioral changes caused by experiences - is a central prerequisite for the development of humans, animals, and some artificial agents. Against the backdrop of psychological and educational theories of learning and related empirical studies, the talk addresses the following questions: How is learning influenced by social

PI Lecture

Klaus Obermayer (SCIoI): Reward-based Learning and Decision Making under Risk

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Reward-based Learning and Decision Making under Risk Reinforcement learning provides a framework for making agents learn policies through feedback signals (“rewards”), which provide information about whether their actions or action sequences were successful or not. Reinforcement learning also provides a framework for understanding how humans learn and decide given reward information only. Standard reinforcement learning

PI Lecture

Oliver Brock (SCIoI): Genesis, Goals, and Gossip of SCIoI

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Abstract: I would like to give a personal perspective of the scientific motivation and framing of SCIoI and relate them to the research of my lab, the Robotics and Biology Laboratory. But at the same time, I would like to critically question and discuss all of these things, in an attempt to move towards a

PI Lecture

Lars Lewejohann (SCIoI): What’s on a mouse’s mind? Behavioral measures to understand animal’s experiences and needs

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What's on a mouse's mind? Behavioral measures to understand animal’s experiences and needs Lars Lewejohann, Freie Universität Berlin, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R) Abstract: Mice, as all other living creatures, have adapted to specific living conditions in the course of evolution. From our human

PI Lecture

Pawel Romanczuk (SCIoI): Collective Information Processing – From Simple Flocking Models to Real Ecological Systems

On ZOOM (Contact us for Link)

Collective Information Processing - From Simple Flocking Models to Real Ecological Systems Abstract: Collective systems such animal groups or cellular ensembles represent fascinating examples of self-organization in biology. In contrast to non-living physical systems, self-organized biological collectives are results of long-term evolutionary adaptations to a specific ecological niche, where collective behavior provides evolutionary benefits to

PI Lecture

Ralph Hertwig: Experimenting with Intelligence

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Experimenting with Intelligence Abstract. Within just 7 years, behavioral decision research in psychology underwent a dramatic change. In 1967, Peterson and Beach (1967a) reviewed more than 160 experiments concerned with people’s statistical intuitions. Invoking the metaphor of the mind as an intuitive statistician, they concluded that “probability theory and statistics can be used as the

PI Lecture

Olaf Hellwich

The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

PI Lecture

Rasha Abdel Rahman, “How intelligent is visual perception?”

Visual perception is shaped by the input from our physical environment and by expectations derived from our sensory experience with the visual world. But is what we see also influenced by higher cognitive capacities such as memories, language, semantic knowledge or (true or false) beliefs? And if so, what are the consequences on how we

PI Lecture

Oliver Brock (Science of Intelligence): 5 Things I Think About (Out Loud)

Abstract: Oliver Brock will talk about these five things: 1) Is intelligence non-decomposable? 2) Does intelligence require multiple computational paradigms? 3) To neuroscience or not to neuroscience? 4) A principle of intelligence? 5) It's all about the prior Each section will be followed by Q&A&D. The Zoom Link will be sent the day before the

PI Lecture

Oliver Brock (Science of Intelligente): 5 Things I Think About (Out Loud), Part 2

Abstract: Oliver Brock will continue exploring about these five things: 1) Is intelligence non-decomposable? 2) Does intelligence require multiple computational paradigms? 3) To neuroscience or not to neuroscience? 4) A principle of intelligence? 5) It’s all about the prior The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)