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DTSTART;TZID=Europe/Berlin:20200206T160000
DTEND;TZID=Europe/Berlin:20200206T173000
DTSTAMP:20260409T193142
CREATED:20200202T165607Z
LAST-MODIFIED:20250604T100838Z
UID:6750-1581004800-1581010200@www.scienceofintelligence.de
SUMMARY:John-Dylan Haynes (SCIoI): “What Can Neuroimaging Tell Us About Human Intelligence?”
DESCRIPTION:The concept of intelligence in cognitive science has been highly elusive. One pragmatic approach to understanding intelligence is to use classical intelligence tests\, such as the Wechsler Adult Intelligence Scale (WAIS). In such tests\, performance is assessed in a number of specific subtask items\, and the performance across these items is then integrated to an overall (or “full scale”) IQ. Neuroimaging has contributed to both the single-item and the full-scale performance. At the item level\, several studies have looked at resource and efficiency models. At the full-scale level studies have looked at overall brain structure\, as well as the importance of various subregions of the brain. Furthermore\, various architectural principles can be considered. Overall\, this line of research contributes to the understanding of intelligent cognition in a specific biological substrate\, the healthy human brain. \nProf. John-Dylan Haynes \nCharité – Universitätsmedizin Berlin\, HU Berlin\, Psychology \n\n\n 
URL:https://www.scienceofintelligence.de/event/pi-lecture-series-john-dylan-haynes-what-can-neuroimaging-tell-us-about-human-intelligence/
LOCATION:MAR23 4.064\, Marchstraße 23\, Berlin\, 10587\, Germany
CATEGORIES:PI Lecture
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200213T160000
DTEND;TZID=Europe/Berlin:20200213T173000
DTSTAMP:20260409T193142
CREATED:20200129T150658Z
LAST-MODIFIED:20250604T100827Z
UID:6694-1581609600-1581615000@www.scienceofintelligence.de
SUMMARY:Henry Shevlin\, Leverhulme Centre for the Future of Intelligence: General Intelligence: An Ecumenical Heuristic for Artificial Consciousness Research?
DESCRIPTION:Henry Shevlin is a research associate at the Leverhulme Centre for the Future of Intelligence (Cambridge).\nHe did his PhD at CUNY Graduate Center in New York with a thesis on “Consciousness\, Perception and Short-Term Memory”. \nLink to CV here \nABSTRACT: \nThe science of consciousness has made great strides in recent decades\, both in the development of theoretical frameworks and in the refinement of our experimental and clinical tools for the assessment of consciousness in humans. However\, the proliferation of competing theories makes it harder to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude\, we may soon face practical and ethical questions about whether\, for example\, an artificial agent is capable of suffering. Moreover\, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial systems. With these challenges in mind\, I propose that we adopt an ecumenical heuristic for artificial consciousness so that we can make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such a heuristic should have three main features: it should be intuitively plausible\, theoretically neutral\, and scientifically tractable. I claim that the concept of general intelligence – understood as a capacity for robust\, flexible\, and integrated cognition and behaviour – satisfies these criteria and may thus provide the basis for such a heuristic\, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious. \nLecture hosted by: Miriam Kyselo
URL:https://www.scienceofintelligence.de/event/henry-shevlin-leverhulme-centre-for-the-future-of-intelligence/
LOCATION:MAR23 4.064\, Marchstraße 23\, Berlin\, 10587\, Germany
CATEGORIES:PI Lecture
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200219T173000
DTEND;TZID=Europe/Berlin:20200219T190000
DTSTAMP:20260409T193142
CREATED:20200122T164401Z
LAST-MODIFIED:20250604T100816Z
UID:6539-1582133400-1582138800@www.scienceofintelligence.de
SUMMARY:“The Ethics of AI-Chemy – When Science Meets Hype” – Keynote Lecture by Prof. Dr. Oliver Brock
DESCRIPTION:Winter School Keynote Lecture: Oliver Brock (Cluster Science of Intelligence\, TU Berlin)\nCluster Speaker Prof. Dr. Oliver Brock will deliver the keynote lecture at this year’s Winter School Ethics and Neuroscience. \n\nThe 9th Winter School “Ethics and Neuroscience is organized by the BCCN Berlin/ICCN and the Berlin School of Mind and Brain. \nThe event is tailored for MSc and PhD students\, but covers a range of topics of potential interest to other researchers\, reflecting \non the ethical and societal consequences of modern neuroscience. \n\nTheoretical foundations\, as well as practical and ethical aspects are addressed. Participants will benefit from a combination of lectures with \ngroup work and discussions\, where they will put the learned content into practice. \nRead more here \n  \n  \n  \nVenue:Humboldt-Universität zu Berlin\nInstitut für Biologie\, Campus Nord\, House 2\, Lecture Hall 1\nEntry to Campus from: Luisenstraße 56\, 10117 Berlin\nEntry to Campus from: Philippstraße 12/13a\, 10115 Berlin \nContact: Dr. Dirk Mende\, Berlin School of Mind and Brain\n030 / 2093-89768
URL:https://www.scienceofintelligence.de/event/the-ethics-of-ai-chemy-when-science-meets-hype-keynote-lecture-by-prof-dr-oliver-brock/
LOCATION:HU Berlin – Institut für Biologie\, Phillipstraße 12/13a\, Berlin\, Berlin\, 10115\, Germany
CATEGORIES:PI Lecture
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200220T100000
DTEND;TZID=Europe/Berlin:20200220T110000
DTSTAMP:20260409T193142
CREATED:20200124T140641Z
LAST-MODIFIED:20250604T100806Z
UID:6566-1582192800-1582196400@www.scienceofintelligence.de
SUMMARY:Pascal Klink (TU Darmstadt): Self-Paced Reinforcement Learning
DESCRIPTION:Thursday Morning Lectures\nAbstract:\nGeneralization 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 benefits of structured\, sequential learning. We introduce a novel relative entropy reinforcement learning algorithm that gives the agent the freedom to control the intermediate task distribution\, allowing for its gradual progression towards the target context distribution. Empirical evaluation shows that the proposed curriculum learning scheme drastically improves sample efficiency and enables learning in scenarios with both broad and sharp target context distributions in which classical approaches perform sub-optimally.\n \nBio:\nPascal is a Ph.D. student at the Intelligent Autonomous Systems (IAS) Group at TU Darmstadt. At IAS\, he works for the ROBOLEAP project\, where he develops methods for reinforcement learning in unstructured\, partially observable real world environments. Before starting his PhD\, Pascal completed his Bachelor’s degree in Computer Science and Master’s degree in Autonomous Systems at the TU Darmstadt. Within his Master’s thesis he worked on “Generalization and Transferability in Reinforcement Learning” and was supervised by Hany Abdulsamad\, Boris Belousov and Jan Peters
URL:https://www.scienceofintelligence.de/event/pascal-klink-tu-darmstadt-self-paced-reinforcement-learning/
LOCATION:MAR23 4.064\, Marchstraße 23\, Berlin\, 10587\, Germany
CATEGORIES:PI Lecture
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