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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251204T100000
DTEND;TZID=Europe/Berlin:20251204T103000
DTSTAMP:20260513T194505
CREATED:20250429T092831Z
LAST-MODIFIED:20251118T101401Z
UID:24523-1764842400-1764844200@www.scienceofintelligence.de
SUMMARY:POSTPONED: Arianna Novati (Science of Intelligence)\, "Mouse Lock Box 2.0"
DESCRIPTION:More details to follow. \n©SCIoI/Katharina Hohlbaum\, Arianna Novati
URL:https://www.scienceofintelligence.de/event/arianna-novati-science-of-intelligence-mouse-lock-box-2-0/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/p46_lockbox1.2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251127T100000
DTEND;TZID=Europe/Berlin:20251127T110000
DTSTAMP:20260513T194505
CREATED:20250429T091138Z
LAST-MODIFIED:20251111T101901Z
UID:24503-1764237600-1764241200@www.scienceofintelligence.de
SUMMARY:Sole Traverso (Science of Intelligence)\, "Symmetry-aware Lifelong Bayesian Reinforcement Learning: Finding the Loo Faster"
DESCRIPTION:More details to follow. \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/sole-traverso-science-of-intelligence/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/chatgtp17.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251120T100000
DTEND;TZID=Europe/Berlin:20251120T110000
DTSTAMP:20260513T194505
CREATED:20250429T092250Z
LAST-MODIFIED:20250909T131853Z
UID:24518-1763632800-1763636400@www.scienceofintelligence.de
SUMMARY:Elena Merdjanovska (Science of Intelligence)\, “Efficient Model Learning From Data With Partially Incorrect Labels: Learning From Noisy Labels”
DESCRIPTION:More details to follow. \n  \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/elena-merdjanovska-science-of-intelligence-efficient-model-learning-from-data-with-partially-incorrect-labels-learning-from-noisy-labels/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/SCIoI_Noisy_Labels_V6_FeaturedImage_Size-1024x512-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251030T100000
DTEND;TZID=Europe/Berlin:20251030T110000
DTSTAMP:20260513T194505
CREATED:20250916T113242Z
LAST-MODIFIED:20251020T123036Z
UID:26812-1761818400-1761822000@www.scienceofintelligence.de
SUMMARY:Dimitri Coelho Mollo (Umeå University)\, "Functional Ontologies for AI systems: Tasks\, Mechanisms\, and Capacities"
DESCRIPTION:Abstract \nThe size and complexity of current Deep Artificial Neural Networks pose remarkable challenges to our attempts of explaining and understanding their workings. In this talk\, I put forward a proposal for complementing existing efforts to that aim\, inspired by research on cognitive ontology in philosophy of cognitive science. In particular\, I suggest that\, as much as we need theoretically and empirically grounded categories for cognitive tasks\, cognitive capacities\, and cognitive mechanisms in cognitive science\, we need theoretically and empirically grounded categories for functional tasks\, capacities and mechanisms when studying AI systems. The resulting functional ontologies\, I argue\, can play crucial roles in informing further research in explainable and interpretable AI\, and in refining our understanding of such systems. I illustrate this proposal by examining recent research on the computational mechanisms underlying specific capacities in Large Language Models\, showing how appeal to functional ontologies can further enrich such research.
URL:https://www.scienceofintelligence.de/event/dimitri-coelho-mollo-umea-university-functional-ontologies-for-ai-systems-tasks-mechanisms-and-capacities/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/05/coelho-mollo-dimitri.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251023T100000
DTEND;TZID=Europe/Berlin:20251023T110000
DTSTAMP:20260513T194505
CREATED:20250429T090752Z
LAST-MODIFIED:20250912T113442Z
UID:24499-1761213600-1761217200@www.scienceofintelligence.de
SUMMARY:Félicie Dhellemmes and Valerii Chirkov (Science of Intelligence)\, "Navigating the Explore-Exploit Trade Off in Collective Search"
DESCRIPTION:More details to follow. \n  \nPhoto by Prince Patel on Unsplash.
URL:https://www.scienceofintelligence.de/event/felicie-dhellemmes-and-valerii-chirkov-science-of-intelligence-navigating-the-explore-exploit-trade-off-in-collective-search/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/Screenshot-2025-04-29-110714.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20251016T100000
DTEND;TZID=Europe/Berlin:20251016T110000
DTSTAMP:20260513T194505
CREATED:20250429T092030Z
LAST-MODIFIED:20251006T100154Z
UID:24515-1760608800-1760612400@www.scienceofintelligence.de
SUMMARY:Anna Lange and Helene Ackermann (Science of Intelligence)\, “Adaptivity in Learner-Teacher Interaction”
DESCRIPTION:More details to follow.
URL:https://www.scienceofintelligence.de/event/anna-lange-and-helene-ackermann-science-of-intelligence-adaptivity-in-learner-teacher-interaction/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/10/Copy-of-zp-TU-HU-ExcelenzForschung-20240122-077___-scaled-e1729865955744.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250925T100000
DTEND;TZID=Europe/Berlin:20250925T230000
DTSTAMP:20260513T194505
CREATED:20250912T140413Z
LAST-MODIFIED:20250922T204359Z
UID:26786-1758794400-1758841200@www.scienceofintelligence.de
SUMMARY:Simon Vock (Charité Universitätsmedizin)\, "Critical dynamics governs deep learning"
DESCRIPTION:Artificial intelligence has advanced rapidly through larger and deeper neural networks\, yet fundamental questions remain about how to optimize network dynamics for performance and adaptability. This study shows that deep neural networks (DNNs)\, like biological brains\, perform optimally when operating near a critical phase transition – poised between active and inactive dynamics. Drawing from physics and neuroscience\, we demonstrate that criticality provides a unifying principle linking structure\, dynamics\, and function in DNNs. Analyzing more than 80 state-of-the-art models\, we first report that improvements in accuracy over the past decade coincided with an implicit evolution toward more critical dynamics. Architectural and training innovations unknowingly guided networks toward this optimal regime. Second\, building on these insights\, we develop a training method that explicitly drives networks to criticality\, improving robustness and performance. Third\, we show that fundamental problems in AI\, including loss of performance in deep continual learning\, are caused by loss of criticality and that maintaining criticality rescues performance. This work introduces criticality as a fundamental framework for AI development by emphasizing dynamic optimization alongside scale. It bridges artificial intelligence with physics and biological cortical network function inspiring novel self-tuning strategies in DNNs. The findings offer a theoretically grounded path forward in designing efficient\, adaptable\, and high-performing artificial intelligence systems drawing inspiration from principles observed in biological neural systems. \nImage generated with DALLE by Maria Ott.
URL:https://www.scienceofintelligence.de/event/simon-vock-charite-universitatsmedizin/
LOCATION:Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/chatgtp12.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250911T100000
DTEND;TZID=Europe/Berlin:20250911T110000
DTSTAMP:20260513T194505
CREATED:20250526T094651Z
LAST-MODIFIED:20250902T080023Z
UID:25080-1757584800-1757588400@www.scienceofintelligence.de
SUMMARY:Asieh Daneshi (Science of Intelligence)\, “Is risky behavior contagious?”
DESCRIPTION:More details to follow. \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/asieh-daneshi-behavioral-contagion-in-human-and-artificial-multi-agent-systems/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250724T100000
DTEND;TZID=Europe/Berlin:20250724T110000
DTSTAMP:20260513T194505
CREATED:20250616T105829Z
LAST-MODIFIED:20250723T143455Z
UID:25596-1753351200-1753354800@www.scienceofintelligence.de
SUMMARY:POSTPONED: Alican Mertan (University of Vermont)\, "Morphological Cognition: Evolving Robots Exhibiting Cognitive Behavior without Abstract Controllers"
DESCRIPTION:With the rise of modern deep learning\, neural networks have become an essential part of virtually every artificial intelligence system\, making it difficult to imagine different models for intelligent behavior. In contrast\, nature provides us with many different mechanisms for intelligent behavior\, most of which we have yet to utilize. One such underinvestigated aspect of intelligence is embodiment and the role it plays in intelligent behavior. We suspect that “the unreasonable effectiveness of deep learning” overshadowed the investigation into what bodies mean for intelligence\, especially how they can be a source of intelligent behavior\, as opposed to passively participating in its display.\nTo investigate how bodies alone give rise to intelligent behavior\, we suggest treating bodies not just as an aid to the brain\, but also studying them as doing full cognitive behavior end-to-end. We term such robots that demonstrate cognitive behaviors without an abstract control layer as possessing “morphological cognition”. I will present our initial work on morphological cognition\, where we use simple shape-changing processes to create robots that can perform a range of tasks from locomotion to image classification without any abstract controller (i.e.\, no neural network). \n  \nImage created by Maria Ott with DALL-E
URL:https://www.scienceofintelligence.de/event/alican-mertan-university-of-vermont-morphological-cognition-evolving-robots-exhibiting-cognitive-behavior-without-abstract-controllers/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250717T100000
DTEND;TZID=Europe/Berlin:20250717T100000
DTSTAMP:20260513T194505
CREATED:20250623T124834Z
LAST-MODIFIED:20250716T123207Z
UID:25730-1752746400-1752746400@www.scienceofintelligence.de
SUMMARY:Matthias Nau (Vrije Universiteit Amsterdam)\, "Revealing General Principles Underlying Active Vision and Memory"
DESCRIPTION:Abstract:\nCognitive neuroscience seeks theories that jointly explain behavioral\, neural\, and mental states. The dominant approach is to use specialized tasks designed to optimally probe a concept of interest (e.g.\, episodic memory)\, and to disentangle behavioral\, sensory\, and mnemonic factors through design (e.g.\, by constraining gaze during image recognition). I will present an alternative framework that instead recognizes that concepts such as perception\, memory\, and action are often inextricable\, both theoretically and empirically\, which I demonstrate for example by showing that brain activity during movie viewing and recall is linked through eye movements. I will argue that new generalizable concepts are needed to explain phenomena across domains\, and outline how such concepts may be empirically derived through multi-task studies: by testing generalization of results across tasks and data modalities\, we reveal the mutual constraints task demands impose on behavioral\, neural\, and mental states. In this context\, I will also highlight the importance of ‘naturalistic’ tasks and behavioral tracking for cognitive neuroscience\, and briefly introduce open-source tools for camera-free MR-based eye tracking. \nImage created by Maria Ott with DALL-E.
URL:https://www.scienceofintelligence.de/event/matthias-nau-vrije-universiteit-amsterdam/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250703T100000
DTEND;TZID=Europe/Berlin:20250703T110000
DTSTAMP:20260513T194505
CREATED:20250429T085710Z
LAST-MODIFIED:20250603T123649Z
UID:24490-1751536800-1751540400@www.scienceofintelligence.de
SUMMARY:Raina Zakir (Université Libre De Bruxelles)\, “Robust Decision-Making in Minimalistic Robot Swarms Under Social Noise”
DESCRIPTION:Abstract \nMinimalistic robot swarms hold great promise for applications in healthcare\, disaster response\, and environmental monitoring. A key challenge lies in enabling these robots to rapidly and reliably reach consensus using limited communication\, computation\, and memory. In this talk\, we explore how robot swarms can collectively identify the best among multiple discrete options in their environment. We analyze and compare several prominent decision-making algorithms through both simulations and theoretical modeling. Particular attention is given to how asocial behaviors—introducing social noise—affect convergence and robustness. Our results offer insights into designing simple yet effective voting rules for robust consensus in decentralized swarm systems. \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/raina-zakir-universite-libre-de-bruxelles/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250626T100000
DTEND;TZID=Europe/Berlin:20250626T110000
DTSTAMP:20260513T194505
CREATED:20250429T085415Z
LAST-MODIFIED:20250616T083952Z
UID:24486-1750932000-1750935600@www.scienceofintelligence.de
SUMMARY:Max Ploner (Science of Intelligence)\, “Evaluating Sample Efficiency: How Language Models Learn to Recall Facts from Data"
DESCRIPTION:More details to follow. \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/max-ploner-modeling-neurogenesis-for-continuous-learning/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250605T100000
DTEND;TZID=Europe/Berlin:20250605T110000
DTSTAMP:20260513T194505
CREATED:20250429T084014Z
LAST-MODIFIED:20250603T123901Z
UID:24475-1749117600-1749121200@www.scienceofintelligence.de
SUMMARY:Palina Bartashevich and David Bierbach (Science of Intelligence)\, “Collective Air Breathing In the Largest Freshwater Fish on Earth”
DESCRIPTION:More details to follow. \nPhoto by David Clode on Unsplash.
URL:https://www.scienceofintelligence.de/event/palina-bartashevich-and-david-bierbach-collective-air-breathing-in-the-largest-freshwater-fish-on-earth/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250522T100000
DTEND;TZID=Europe/Berlin:20250522T110000
DTSTAMP:20260513T194505
CREATED:20250402T100239Z
LAST-MODIFIED:20250516T125303Z
UID:24002-1747908000-1747911600@www.scienceofintelligence.de
SUMMARY:Anne Jaap\, Friedrich Schüßler\, and Paul Mieske (Science of Intelligence): "Big mouse data: Characterizing mouse behavior through temporal statistics"
DESCRIPTION:The study of animal behavior is rapidly changing due to recent advances in long-term recording and automated analysis. Here we use these new developments to characterize mouse behavior via their temporal statistics. We analyzed positional data (RFID detections) of groups of mice housed in complex environments over many months. We found that behavior spanning seconds to hours can be separated into three distinct temporal ranges or states: short states of up to 2 min\, that correspond mostly to explorative and interactive behaviors; intermediate states between 2-20 min\, consisting mostly of feeding and grooming; and long states beyond 20 min corresponding to sleep. Each state has a simple statistical description that allows for a simple model to recapture the broad aspects of the data. We further characterized these states across individuals and age and showed that the amount spent in each state is homeostatically controlled. Taken together\, we uncovered a surprisingly simple and consistent description of the temporal statistics of behavior in mice. Our results open up new questions about the underlying mechanisms as well as similar characterizations in other species. \n  \nPhoto courtesy of SCIoI Project 40.
URL:https://www.scienceofintelligence.de/event/anne-jaap-friedrich-schusler-paul-mieske-big-mouse-data/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250515T100000
DTEND;TZID=Europe/Berlin:20250515T110000
DTSTAMP:20260513T194505
CREATED:20250317T111923Z
LAST-MODIFIED:20250603T123939Z
UID:23749-1747303200-1747306800@www.scienceofintelligence.de
SUMMARY:David Bierbach & Yunus Sevinchan (Science of Intelligence)\, “Self-Organised Criticality in Animal Collectives”
DESCRIPTION:More details to follow. \n  \nPhoto by lance Anderson on Unsplash.
URL:https://www.scienceofintelligence.de/event/david-bierbach-yunus-sevinchan-science-of-intelligence-self-organised-criticality-in-animal-collectives/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/03/lance-anderson-G2SDLsJp3rg-unsplash-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250424T100000
DTEND;TZID=Europe/Berlin:20250424T110000
DTSTAMP:20260513T194505
CREATED:20250317T105402Z
LAST-MODIFIED:20250603T124043Z
UID:23736-1745488800-1745492400@www.scienceofintelligence.de
SUMMARY:Adrien Doerig (Freie Universität)\, “High-Level Visual Representations in the Human Brain Are Aligned With Large Language Models”
DESCRIPTION:The human brain extracts complex information from visual inputs\, including objects\, their spatial and semantic interrelations\, and their interactions with the environment. However\, a quantitative approach to capture this information remains elusive. I will present work where we show that LLM embeddings of scene captions successfully characterise brain activity evoked by viewing the natural scenes. This mapping captures selectivities of different brain areas\, and is sufficiently robust that accurate scene captions can be reconstructed from brain activity. Further\, we show that neural networks trained to transform image inputs into LLM representations are better aligned with brain representations than a large number of state-of-the-art alternative models\, despite being trained on orders-of-magnitude less data. Overall\, these results suggest that LLM embeddings of scene captions provide a representational format that accounts for complex information extracted by the brain from visual inputs. \nPhoto created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/adrien-doerig-freie-universitat-high-level-visual-representations-in-the-human-brain-are-aligned-with-large-language-models/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250417T100000
DTEND;TZID=Europe/Berlin:20250417T113000
DTSTAMP:20260513T194505
CREATED:20250317T105203Z
LAST-MODIFIED:20250603T124106Z
UID:23733-1744884000-1744889400@www.scienceofintelligence.de
SUMMARY:Tamal Roy & Valentin Lecheval (Science of Intelligence)\, “Evolution of Collective Cognition Through Individual-Level Selection”
DESCRIPTION:More details to follow. \nPhoto created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/tamal-roy-valentin-lechecal-science-of-intelligence-evolution-of-collective-cognition-through-individual-level-selection/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250410T100000
DTEND;TZID=Europe/Berlin:20250410T110000
DTSTAMP:20260513T194505
CREATED:20250317T104720Z
LAST-MODIFIED:20250603T124113Z
UID:23728-1744279200-1744282800@www.scienceofintelligence.de
SUMMARY:Bojana Grujičić (Science of Intelligence)\, "Artificial Possibilities"
DESCRIPTION:Science often deals with issues pertaining to possibilities\, contingencies and necessities\, by engaging in thought experiments and modeling. This talk discusses how much deep learning can be helpful for navigating the possibility space for intelligence\, adding to our scientific understanding of possibilities. One epistemically useful feature of neural networks is their runnability – they can be trained to perform a cognitive task and can run when given novel stimuli\, demonstrating possibilities of cognitive phenomena based on sets of inductive biases. I focus on the problem of justification of neural network-based inferences about possibilities and outline a plausible justificatory strategy. I consider a number of reasons for taking neural network-demonstrated possibilities to be technological\, rather than biological possibilities. Despite this\, I argue that they add to our scientific understanding of possibilities related to intelligence. \n  \nPhoto by Joakim Honkasalo on Unsplash.
URL:https://www.scienceofintelligence.de/event/bojana-grucic-science-of-intelligence-artificial-possibilities/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250327T100000
DTEND;TZID=Europe/Berlin:20250327T110000
DTSTAMP:20260513T194505
CREATED:20250210T105859Z
LAST-MODIFIED:20250303T121007Z
UID:23394-1743069600-1743073200@www.scienceofintelligence.de
SUMMARY:Vito Trianni (Institute of Cognitive Sciences and Technologies\, CNR Rome)\, "Emergence and Heterogeneity in Minimalist Robot Swarms"
DESCRIPTION:Far-reaching perspectives in swarm robotics consider robots that are minimalist in their sensing\, communication and computation\, but are deployed in thousands to collaborate towards the accomplishment of tasks distributed in space and time. Generally speaking\, future robot swarms might face harsh operating conditions where little communication is possible and no external infrastructure is available. These robots might not be able to efficiently communicate with a central controller and might not have the perceptual and computational abilities to self-localise or precisely plan their movements. It is therefore necessary to study collaborative strategies that do not rely on complex control and interaction rules. In this talk\, I will present studies about minimalist approaches to collective behaviours based on random walks and simple communication systems. I will introduce the concept of Adaptive Random Walks as a tool to design simple emergent behaviours in minimalist robot swarms\, and present the case of team formation and aggregation\, showing how heterogeneity in the swarm can be beneficial to improve efficiency while maintaining the complexity low. I will then discuss minimal quorum sensing strategies\, and discuss which communication protocol provide benefits for group coordination. \n  \nPhoto by Christopher Burns on Unsplash
URL:https://www.scienceofintelligence.de/event/vito-trianni-institute-of-cognitive-sciences-and-technologies-cnr-rome/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250320T100000
DTEND;TZID=Europe/Berlin:20250320T110000
DTSTAMP:20260513T194505
CREATED:20250210T105744Z
LAST-MODIFIED:20250603T124131Z
UID:23390-1742464800-1742468400@www.scienceofintelligence.de
SUMMARY:Konstantinos Voudouris (Helmholtz AI\, University of Cambridge)\, “ What Are AI Capabilities and How Can We Measure Them?”
DESCRIPTION:What can AI systems do? Answering this question requires us to model their capabilities\, but this first demands a clear conception of what capabilities are and which tools we can use to measure them. I advance a dispositional account of capabilities\, understanding them as a system’s propensity to behave in certain ways under certain conditions. I then survey the tools we have at our disposal to measure capabilities\, and what the nascent field of AI Evaluation can learn from the broader cognitive sciences. \n  \nPhoto by Stefan Cosma on Unsplash
URL:https://www.scienceofintelligence.de/event/konstantinos-voudouris-helmholtz-ai-university-of-cambridge-capability-measurement-in-llms/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/02/stefan-cosma-GVlcXhQejA8-unsplash-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250313T100000
DTEND;TZID=Europe/Berlin:20250313T110000
DTSTAMP:20260513T194505
CREATED:20250210T103933Z
LAST-MODIFIED:20250603T124142Z
UID:23386-1741860000-1741863600@www.scienceofintelligence.de
SUMMARY:Jonas Kuckling (University of Konstanz)\, “Living on the Edge – Scalability and Two-Phase Performance in Multi-Robot Systems”
DESCRIPTION:Scalability is often lauded as one of the advantages of decentralized multi-robot systems and robot swarms. Theory and many experimental works predict that with increasing swarm density\, we will observe a gradual decay of performance. In our work\, we have taken a closer look at the scalability of robot swarms in different settings and we have noticed that the predicted decay does not always appear to be gradual. Instead\, the performance splits into two phases\, potentially causing catastrophic failures at near-optimal swarm densities. In this talk\, I will provide an overview of our empirical and theoretical analyses of scalability behavior in robot swarms and the resulting considerations for the design of robot swarms. \n  \nImage created in DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/jonas-kuckling-university-of-konstanz/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/webp:https://www.scienceofintelligence.de/wp-content/uploads/2025/02/Giovanni_Mohsen.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250220T100000
DTEND;TZID=Europe/Berlin:20250220T110000
DTSTAMP:20260513T194505
CREATED:20250113T125547Z
LAST-MODIFIED:20250603T124213Z
UID:23115-1740045600-1740049200@www.scienceofintelligence.de
SUMMARY:Julten Abdelhalim\, “Mastering Confident & Quick-Witted Communication in Academia” Workshop
DESCRIPTION:In this one-hour workshop\, a toolbox of best-practise techniques for confident communication skills will be presented. This will equip attendees with a repertoire of rhetorical tools to communicate confidently and quick-wittedly in stressful situations. Participants will learn strategies to handle challenging questions and optimise their performance during academic debates. Another aim is to tackle dealing with harsh criticism\, personal attacks and knock-down arguments.
URL:https://www.scienceofintelligence.de/event/julten-abdelhalim-mastering-confident-quick-witted-communication-in-academia-workshop/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/05/abdelhalim-julten.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250213T100000
DTEND;TZID=Europe/Berlin:20250213T110000
DTSTAMP:20260513T194505
CREATED:20250108T103243Z
LAST-MODIFIED:20250603T124226Z
UID:23032-1739440800-1739444400@www.scienceofintelligence.de
SUMMARY:Marina Papadopoulou (University of Tuscia)\, “Behavioural Rules Underlying Self-Organized Animal Collectives”
DESCRIPTION:From the foraging of ungulates and primates to the bait balls of fish and the murmurations of starlings\, the dynamics of animal groups fascinate us with the mystery of their underlying social interactions. Identifying unique and common traits across systems can help us understand the self-organized mechanisms of their emergence\, as well as the ecological and evolutionary processes that shape this diversity. In this talk\, I will showcase ongoing projects on the collective behaviour of several species of vertebrates\, such as schools of Amazon mollies\, flocks of European starlings\, and troops of chacma baboons\, aiming to understand the cognitive rules involved in the dynamics of these collectives. Specifically\, I will focus on inter- and intra- specific variation in collective motion and decision-making\, the role of individual heterogeneity\, and the emergence of complex patterns of collective escape\, with methodological details on the analysis of empirical data\, the use of robotic predators and conspecifics\, and the development of data-inspired agent-based models. \nPhoto by Marek Piwnicki on Unsplash
URL:https://www.scienceofintelligence.de/event/marina-papadopoulou-university-of-tuscia-behavioural-rules-underlying-self-organized-animal-collectives/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/01/marek-piwnicki-8SqgP2vIwJk-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250123T100000
DTEND;TZID=Europe/Berlin:20250123T110000
DTSTAMP:20260513T194505
CREATED:20250106T100435Z
LAST-MODIFIED:20250603T124327Z
UID:22994-1737626400-1737630000@www.scienceofintelligence.de
SUMMARY:Wannes Ooms (KU Leuven Centre for IT & IP Law -Imec): A General Introduction to the EU AI Act
DESCRIPTION:The EU AI Act introduces new obligations for providers and deployers of AI systems. In this presentation\, we will discuss the scope of the AI Act\, the different qualifications of AI systems under the act and the related obligations or requirements. We also provide a look ahead at key deadlines\, the status of standards and conformity assessments\, and other responsibilities along the AI value chain. \nThis event will take place in person and will be streamed via zoom. \nPhoto by Alex Knight on Unsplash
URL:https://www.scienceofintelligence.de/event/wannes-ooms-ku-leuven-centre-for-it-ip-law-imec-a-general-introduction-to-the-eu-ai-act/
LOCATION:Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/01/alex-knight-2EJCSULRwC8-unsplash-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250116T100000
DTEND;TZID=Europe/Berlin:20250116T110000
DTSTAMP:20260513T194505
CREATED:20250106T095531Z
LAST-MODIFIED:20250107T153234Z
UID:22991-1737021600-1737025200@www.scienceofintelligence.de
SUMMARY:Anita Keshmirian (Forward College\, Berlin): "Many Minds\, Diverging Morals: Human Groups vs. AI in Moral Decision-Making"
DESCRIPTION:Moral judgments are inherently social\, shaped by interactions with others in everyday life. Despite this\, psychological research has rarely examined the impact of social interactions on these judgments. In our study\, we explored the role of group dynamics in moral decision-making by having small groups (4-5 participants) evaluate moral dilemmas first individually\, then collectively\, and finally individually a second time. Participants judged real-life and sacrificial moral dilemmas involving actions or inactions violating moral principles to benefit the greater good. Experiment 1 found that collective judgments were more utilitarian than individual judgments\, supporting the hypothesis that group deliberation temporarily reduces the emotional burden of violating moral norms. \nExperiment 2 measured participants’ state anxiety and moral judgments before\, during\, and after online interactions. Results again showed that collectives were more utilitarian\, reducing state anxiety during and after social interaction\, suggesting that stress reduction may explain the shift toward utilitarianism in group settings. We replicated this experiment using multi-agent large language models (LLMs) to test how artificial agents make moral decisions. Preliminary findings revealed that\, unlike humans\, groups of LLM agents were less utilitarian than individual agents. Analysis of the agents’ interactions showed a consistent pattern of virtue-signaling\, with LLMs emphasizing deontological reasoning (focusing on moral rules) rather than utilitarian principles. \nThis divergence from human behavior suggests that collective reasoning in AI systems is shaped by different dynamics\, likely due to how LLMs are trained to prioritize socially accepted norms. These results highlight important differences in moral decision-making between human and artificial intelligence\, offering new insights into the development of AI systems that more closely mirror human ethical reasoning\, particularly in complex\, real-world collective decision-making scenarios. \nImage created with DALL-E by Maria Ott
URL:https://www.scienceofintelligence.de/event/anita-keshmirian-many-minds-diverging-morals-human-groups-vs-ai-in-moral-decision-making/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/webp:https://www.scienceofintelligence.de/wp-content/uploads/2025/01/TMT_Anita_Keshmirian-2-e1736256383948.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20241128T100000
DTEND;TZID=Europe/Berlin:20241128T110000
DTSTAMP:20260513T194505
CREATED:20240911T084638Z
LAST-MODIFIED:20250603T124540Z
UID:22176-1732788000-1732791600@www.scienceofintelligence.de
SUMMARY:Hideki Kozima (Tohoku University)\, “Child-Robot Interactions for Therapeutic and Educational Research and Practices”
DESCRIPTION:Abstract:\nResearch in developmental robotics includes modeling human intelligence and the process of its emergence in robotic systems. A novel research paradigm in psychology is emerging in conjunction with such efforts regarding reproducing human-specific communication abilities in robots and observing how children interact with robots with various communication capabilities. I will discuss such research trends from a broader perspective\, and the potential to realize robots that afford children the opportunities to build social relationships is examined. We consider human communication abilities not as a set of interactive functionalities in individuals but as a set of social tools in which functionalities have emerged from the social interaction driven by the individual motivation to form relationships with others. We also explore some representative works on using robots to help establish such relationships in autistic and typically developing children. Finally\, we discuss the possibility of using robots for further research and practical support for child development centered on building social relationships. \n  \nThis talk will take place in person at SCIoI (room 2.057). \n  \nPhoto by Owen Beard on Unsplash.
URL:https://www.scienceofintelligence.de/event/hideki-kozima-tohuku-university/
LOCATION:SCIoI\, Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/09/xkozima-L-gray.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20241031T100000
DTEND;TZID=Europe/Berlin:20241031T110000
DTSTAMP:20260513T194505
CREATED:20241002T101830Z
LAST-MODIFIED:20250603T124704Z
UID:22386-1730368800-1730372400@www.scienceofintelligence.de
SUMMARY:POSTPONED: Anita Keshmirian (Forward College\, Berlin)\, “Many Minds\, Diverging Morals: Human Groups vs. AI in Moral Decision-Making”
DESCRIPTION:Abstract \n“Moral judgments are inherently social\, shaped by interactions with others in everyday life. Despite this\, psychological research has rarely examined the impact of social interactions on these judgments. In our study\, we explored the role of group dynamics in moral decision making by having small groups (4-5 participants) evaluate moral dilemmas first individually\, then collectively\, and finally individually a second time. Participants judged real-life and sacrificial moral dilemmas involving actions or inactions violating moral principles to benefit the greater good. Experiment 1 found that collective judgments were more utilitarian than individual judgments\, supporting the hypothesis that group deliberation temporarily reduces the emotional burden of violating moral norms. Experiment 2 measured participants’ state anxiety and moral judgments before\, during\, and after online interactions. Results again showed that collectives were more utilitarian\, reducing state anxiety during and after social interaction\, suggesting that stress reduction may explain the shift toward utilitarianism in group settings. \nWe replicated this experiment using multi-agent large language models (LLMs) to test how artificial agents make moral decisions. Preliminary findings revealed that\, unlike humans\, groups of LLM agents were less utilitarian than individual agents. Analysis of the agents’ interactions showed a consistent pattern of virtue-signaling\, with LLMs emphasizing deontological reasoning (focusing on moral rules) rather than utilitarian principles. This divergence from human behavior suggests that collective reasoning in AI systems is shaped by different dynamics\, likely due to how LLMs are trained to prioritize socially accepted norms. These results highlight important differences in moral decision-making between human and artificial intelligence\, offering new insights into the development of AI systems that more closely mirror human ethical reasoning\, particularly in complex\, real-world collective decision-making scenarios.” \nImage credit: ©SCIoI/ generated with DALL-E
URL:https://www.scienceofintelligence.de/event/anita-keshmirian-forward-college-berlin-many-minds-diverging-morals-human-groups-vs-ai-in-moral-decision-making/
LOCATION:Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/webp:https://www.scienceofintelligence.de/wp-content/uploads/2024/10/TMT_Image_creativity_artificial2-e1727864193669.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240725T100000
DTEND;TZID=Europe/Berlin:20240725T110000
DTSTAMP:20260513T194505
CREATED:20240719T144755Z
LAST-MODIFIED:20250603T124813Z
UID:21025-1721901600-1721905200@www.scienceofintelligence.de
SUMMARY:Ralf M. Haefner (University of Rochester\, NY)\, “How We Move Our Eyes To Collect Information”
DESCRIPTION:Abstract\nCollecting new information about the outside world is a key aspect of brain function. In the context of vision\, we move our eyes multiple times per second to accumulate evidence about a scene. Prior studies have suggested that this process is goal-directed and close to optimal. Here\, we show that this process of seeking new information suffers from a confirmation bias similar to what has been observed in a wide range of other contexts. We present data from a new gaze-contingent task that allows us to both estimate a participant’s current belief\, and compare that to their subsequent eye-movements. We find that these eye-movements are biased in a confirmatory way. Finally\, we show that these empirical results can be parsimoniously explained under the assumption that the brain performs approximate\, not exact\, inference\, with computations being more approximate in decision-making compared to sensory areas. \nThis talk will take place in person at SCIoI. \n  \nImage created with DALL-E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/ralf-m-haefner-university-of-rochester-ny-how-we-move-our-eyes-to-collect-information/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/webp:https://www.scienceofintelligence.de/wp-content/uploads/2024/07/Ralf-Haefner_1.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240718T100000
DTEND;TZID=Europe/Berlin:20240718T113000
DTSTAMP:20260513T194505
CREATED:20240624T113208Z
LAST-MODIFIED:20250603T124835Z
UID:20867-1721296800-1721302200@www.scienceofintelligence.de
SUMMARY:Adrian Sieler (Science of Intelligence): “Building Anthropomorphic Soft Robotic Hands With Human-Like Manipulation Abilities”
DESCRIPTION:More info to follow. \n  \nThis talk will take place in person at SCIoI.
URL:https://www.scienceofintelligence.de/event/adrian-sieler-science-of-intelligence-building-anthropomorphic-soft-robotic-hands-with-human-like-manipulation-abilities/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/06/20201020-SCIOI-Adrian1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240704T100000
DTEND;TZID=Europe/Berlin:20240704T113000
DTSTAMP:20260513T194505
CREATED:20240506T082117Z
LAST-MODIFIED:20250603T124850Z
UID:19371-1720087200-1720092600@www.scienceofintelligence.de
SUMMARY:Caleb Weinreb (Harvard Medical School)\, “A Seconds-Long Timescale in Naturalistic Behavior Structures Neural Dynamics”
DESCRIPTION:A core task of animal cognition is to carve the world up into relevant contextual states – based on sensory input\, internal drives\, and awareness of one’s own recent behavior – and then hold these state assignments in working memory as guides for action and anchors for learning. By training animals to perform asks with well-defined contextual states\, researchers have homed in on prefrontal cortex (PFC) as a critical node for such contextual state inference. But these tasks are a poor approximation of real life; rather than engaging in a single well-defined task\, free animals define their own tasks and engage in them dynamically over time recognizing contexts that emerge naturally from their own interactions with task affordances. A core question in neuroethology is which specific “task states” emerge in a given experimental setting and how they structure neural dynamics\, including in PFC. We took advantage of motion sequencing (MoSeq) — which uses 3D pose tracking and machine learning to segment behavior into sub-second motifs or “syllables” – to understand how mPFC activity coevolves with behavior across multiple timescales during unconstrained social interaction and solitary exploration. We find mPFC activity correlates strongly with ongoing behavior\, and that these correlations are most parsimoniously explained through an underlying manifold of behavior states that evolve on a timescale of seconds. The behavior states influence not only which PFC neurons are active\, but also which variables are most strongly encoded. We also find that the composition of states is labile and propose that it emerges predictably from the number and salience of affordances in the animal’s environment. \n  \nThis talk will take place in person at SCIoI. \nPhoto by Pietro Jeng on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/caleb-weinreb-harvard-medical-school/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/05/pietro-jeng-n6B49lTx7NM-unsplash-1024x1024-1.jpg
END:VEVENT
END:VCALENDAR