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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250605T100000
DTEND;TZID=Europe/Berlin:20250605T110000
DTSTAMP:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/david-clode-rpA8tpa4QO0-unsplash-1-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250522T100000
DTEND;TZID=Europe/Berlin:20250522T110000
DTSTAMP:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/04/IMG_0942-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250515T100000
DTEND;TZID=Europe/Berlin:20250515T110000
DTSTAMP:20260627T234117
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:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/03/chatgtp17.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250417T100000
DTEND;TZID=Europe/Berlin:20250417T113000
DTSTAMP:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/03/chatgtp5.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250410T100000
DTEND;TZID=Europe/Berlin:20250410T110000
DTSTAMP:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/03/joakim-honkasalo-ssvjJLB6wIw-unsplash-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250327T100000
DTEND;TZID=Europe/Berlin:20250327T110000
DTSTAMP:20260627T234117
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2025/02/christopher-burns-Kj2SaNHG-hg-unsplash-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250320T100000
DTEND;TZID=Europe/Berlin:20250320T110000
DTSTAMP:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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:20260627T234117
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240613T100000
DTEND;TZID=Europe/Berlin:20240613T113000
DTSTAMP:20260627T234117
CREATED:20240530T134836Z
LAST-MODIFIED:20250603T124915Z
UID:20720-1718272800-1718278200@www.scienceofintelligence.de
SUMMARY:Aravind Battaje (Science of Intelligence)\, “A Study on Human and Robot Perception and the Architecture of Perceptual Information Processing”
DESCRIPTION:More details to follow. \n  \nThis talk will take place in person at SCIoI. \nPhoto by Markus Spiske on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/aravind-battaje-a-study-on-human-and-robot-perception-and-the-architecture-of-perceptual-information-processing/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240530T100000
DTEND;TZID=Europe/Berlin:20240530T110000
DTSTAMP:20260627T234117
CREATED:20240424T083921Z
LAST-MODIFIED:20240813T103215Z
UID:19215-1717063200-1717066800@www.scienceofintelligence.de
SUMMARY:Verena Wagner (University of Konstanz)\, “On Pause: Suspending Judgment and Abstaining in Machine Learning”
DESCRIPTION:Abstract:\n\nMachine Learning (ML) systems typically yield definitive outputs\, even when the underlying probabilities do not justify a decision. This poses a significant challenge in medical applications\, where patients rely on individualized diagnoses\, treatments\, and prognoses. A recent advancement in ML research addresses this issue by introducing so-called “abstention models\,” which enable ML systems to provide neutral outputs. From the perspective of a philosopher who works on cognitive neutrality and the suspension of judgment in human agents\, this is an interesting field to explore. In this talk\, I will introduce my philosophical theory of cognitive neutrality\, which promotes various ways of suspending judgment. Against this backdrop\, I will explore different abstention models and look for similarities and differences between suspension of judgment in humans and abstention in ML systems. In particular\, I will examine whether the distinctions outlined in my cognitive neutrality framework also manifest in different models of abstention. \n  \n\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Markus Spiske on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/verena-wagner-university-of-konstanz-on-pause-suspending-judgment-and-abstaining-in-machine-learning/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240523T100000
DTEND;TZID=Europe/Berlin:20240523T110000
DTSTAMP:20260627T234117
CREATED:20240424T114021Z
LAST-MODIFIED:20250603T124944Z
UID:19227-1716458400-1716462000@www.scienceofintelligence.de
SUMMARY:Asieh Daneshi\, “The Effect of Group Size and Group Density on Behavioral Contagion in Humans”
DESCRIPTION:More details to follow. \n  \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/asieh-daneshi-the-effect-of-group-size-and-group-density-on-behavioral-contagion-in-humans/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240516T100000
DTEND;TZID=Europe/Berlin:20240516T110000
DTSTAMP:20260627T234117
CREATED:20240424T113512Z
LAST-MODIFIED:20250603T124959Z
UID:19222-1715853600-1715857200@www.scienceofintelligence.de
SUMMARY:Alicia Burns\, “Predator-Prey Interactions in the Open Ocean”
DESCRIPTION:More details to follow. \nThis talk will take place in person at SCIoI. \nPhoto by: Rodrigo Friscione Wyssmann. \n 
URL:https://www.scienceofintelligence.de/event/shepherding-behaviour-in-predator-prey-interactions-p33/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240502T100000
DTEND;TZID=Europe/Berlin:20240502T110000
DTSTAMP:20260627T234117
CREATED:20240424T112306Z
LAST-MODIFIED:20240813T103302Z
UID:19218-1714644000-1714647600@www.scienceofintelligence.de
SUMMARY:Joshua B. Evans\, “Creating Multi-Level Skill Hierarchies in Reinforcement Learning”
DESCRIPTION:Abstract:\n\nWhat is a useful skill hierarchy for an autonomous agent? In this talk\, we will consider a possible answer based on a graphical representation of how the interaction between an agent and its environment may unfold. The proposed approach uses modularity maximisation as a central organising principle to expose the structure of the interaction graph at multiple levels of abstraction. The result is a collection of skills that operate at varying time scales\, organised into a hierarchy\, where skills that operate over longer time scales are composed of skills that operate over shorter time scales. The entire skill hierarchy is generated automatically\, with no human intervention\, including the skills themselves (their behaviour\, when they can be called\, and when they terminate) as well as the hierarchical dependency structure between them. In a wide range of environments\, this approach generates skill hierarchies that are intuitively appealing and that considerably improve the learning performance agents given access to them. \n  \n\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Bofu Shaw on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/joshua-b-evans-creating-multi-level-skill-hierarchies-in-reinforcement-learning/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240418T100000
DTEND;TZID=Europe/Berlin:20240418T113000
DTSTAMP:20260627T234117
CREATED:20231113T143920Z
LAST-MODIFIED:20250603T125021Z
UID:18049-1713434400-1713439800@www.scienceofintelligence.de
SUMMARY:Pavel Němec (Charles University)\, “Two Independent Origins of Complex Brains and Intelligent Behavior in Birds and Mammals”
DESCRIPTION:Abstract:\n\nOver the last 20 years\, it has been shown that birds and mammals are startlingly similar in their cognitive repertoire. Even the most intelligent taxa from each group – great apes and large corvids and parrots – match each other in most domains of cognition. This functional similarity is remarkable considering that birds and mammals shared a last common ancestor about 325 million years ago. Moreover\, avian brains are small and lack a cerebral cortex arranged in layers. My talk will focus on recent discoveries showing that birds and mammals independently evolved brains with dramatically increased neuron numbers in the telencephalon and cerebellum\, brain parts associated with higher cognition. This brain information processing capacity surge in birds and mammals is associated with the elaboration of at least partly non-homologous neural circuitry. Moreover\, similar functions are processed in different\, non-homological forebrain regions. Extreme neuron packing densities in birds partly explain why they have similar cognitive levels as mammals\, but volumetrically much smaller brains. Astoundingly\, phylogenetic analysis suggests that as few as four major changes in neuron-brain scaling in over 300 million years of evolution pave the way to intelligence in endothermic land vertebrates. \n\nPh. kindly provided by Pavel Němec. \n\n\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-thursday-morning-talk-pavel-nemec-charles-university-two-independent-origins-of-complex-brains-and-intelligent-behavior-in-birds-and-mammals/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240411T100000
DTEND;TZID=Europe/Berlin:20240411T110000
DTSTAMP:20260627T234117
CREATED:20231113T093715Z
LAST-MODIFIED:20250603T125032Z
UID:17053-1712829600-1712833200@www.scienceofintelligence.de
SUMMARY:Hector Garcia De Marina (University of Granada)\, “Practical Challenges in Formation Control and Mobile Robot Swarms”
DESCRIPTION:Abstract: \nRobot swarms have the potential to assist us with simpler logistics in persistent missions involving vast scenarios. Robot swarms also promise added resilience to complete their objectives despite unforeseen difficulties. However\, current demonstrations of swarm technology in unstructured environments only count on single-digit individuals. That is farther from what one would expect from the huge scaling potential of a swarm. What are the bottlenecks then? \nIn this talk\, I will present some practical challenges that mobile robot swarms face in fundamental tasks\, e.g.\, the control of specific geometry parameters during a swarm deployment\, also known as formation control. As an application of higher-level tasks leveraging formation control\, we will see the coordination of robots while tracking paths and the source-seeking of scalar fields. \nI will also focus on onboard imperfections and how they are responsible for non-designed emergent behavior. Nevertheless\, I will show some hidden opportunities within the imperfections that could assist us with practical deployments. \n\n\nRelated articles (free links to Arxiv):\nManeuvering and robustness issues in undirected displacement-consensus-based formation control: https://arxiv.org/abs/2008.03544\nGuiding vector fields for the distributed motion coordination of mobile robots: https://arxiv.org/abs/2209.09478v4\nResilient source seeking with robot swarms: https://arxiv.org/abs/2309.02937\nBehavioral-based circular formation control for robot swarms: https://arxiv.org/abs/2309.09101\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Louis Reed on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-hector-garcia-de-marina/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240404T100000
DTEND;TZID=Europe/Berlin:20240404T233000
DTSTAMP:20260627T234117
CREATED:20240321T143812Z
LAST-MODIFIED:20240813T103456Z
UID:18046-1712224800-1712273400@www.scienceofintelligence.de
SUMMARY:Jacek Wiland\,  "Assessing the Factual Knowledge Contained in Language Models During Lifelong Learning"
DESCRIPTION:More details to follow.\n\n\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-jacek-wiland-assessing-the-factual-knowledge-contained-in-language-models-during-lifelong-learning/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240328T100000
DTEND;TZID=Europe/Berlin:20240328T113000
DTSTAMP:20260627T234117
CREATED:20240318T143711Z
LAST-MODIFIED:20250603T125108Z
UID:18043-1711620000-1711625400@www.scienceofintelligence.de
SUMMARY:Heiner Spieß (Science of Intelligence)\, “Tools to Study the Generality of Deep Neural Network Representations”
DESCRIPTION:More details to follow.\n\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-heiner-spies-tools-to-study-the-generality-of-deep-neural-network-representations/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240321T100000
DTEND;TZID=Europe/Berlin:20240321T110000
DTSTAMP:20260627T234117
CREATED:20231113T093422Z
LAST-MODIFIED:20240813T103529Z
UID:17052-1711015200-1711018800@www.scienceofintelligence.de
SUMMARY:Fariba Karimi (Graz University of Technology)\, "Complexity Science for Societal Good"
DESCRIPTION:Abstract:\nSocial inequalities — structured and recurrent patterns of unequal distribution of wealth\, opportunities\, and rewards — are on the rise\, and quick-fix\, top-down approaches are failing. Structural inequality is one of the important manifestations of social inequalities in which institutions\, policies\, and societies create systems of privilege that are structural barriers to equality and inclusiveness. Structural inequalities emerge and evolve in complex multi-dimensional social networks. With the rise of artificial intelligence and algorithms in decision-making processes\, such inequalities are being reinforced and exacerbated in a non-linear\, complex manner that is difficult to comprehend and tackle. To address and mitigate such timely issues\, we need a complexity science approach and interdisciplinary teams more than ever.\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Vincentiu Solomon on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-fariba-karimi/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240307T100000
DTEND;TZID=Europe/Berlin:20240307T230000
DTSTAMP:20260627T234117
CREATED:20240124T140430Z
LAST-MODIFIED:20250603T125133Z
UID:18023-1709805600-1709852400@www.scienceofintelligence.de
SUMMARY:Christian Poth (Bielefeld University)\, “Task-Driven Phasic Alertness: How Being Ready for Action Relies on the Current Task”
DESCRIPTION:Abstract:\nHumans often must respond quickly to events happening in their environment. To support fast perception and action\, the brain has evolved a warning system. Warning stimuli are used to elicit a transient state of readiness for perception and action (phasic alertness) that results in faster perceptual processing and faster decision-making for action. Phasic alertenss is assumed to be “unintelligent” in the sense that it is driven by the warning stimuli\, irrespective of the cognitive task set and the expectations guiding goal-directed behavior in the current task. Here\, we review recent findings that falsify this assumption. We provide evidence that phasic alertness presupposes an expectation that stimuli can serve as a warning within the current task. In addition\, we show that within a task\, phasic alertness unfolds in action-focused episodes that restrict its effects to only the next action in an action sequence. Together\, these findings reveal that phasic alertness is not entirely stimulus-based (bottom-up)\, but also relies on the cognitive mechanisms for (top-down) control of task-driven and goal-directed action and thus the “intelligent” interaction with the environment.\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Kirill Pershin on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-christian-poth-bielefeld-university-task-driven-phasic-alertness-how-being-ready-for-action-relies-on-the-current-task/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240222T100000
DTEND;TZID=Europe/Berlin:20240222T110000
DTSTAMP:20260627T234117
CREATED:20240205T134855Z
LAST-MODIFIED:20250603T125157Z
UID:18017-1708596000-1708599600@www.scienceofintelligence.de
SUMMARY:Tim Kietzmann (University of Osnabrück)\, “Large Language Models Offer a Rich Representational Format for Understanding the Transformation of Visual Information in the Human Brain.”
DESCRIPTION:Abstract: Originating from the connectionist movement of cognitive science\, deep neural networks (DNNs) have had tremendous influence on artificial intelligence\, operating at the core of today’s most powerful applications. At the same time\, cognitive computational neuroscientists have recognised their promise to act as “Goldilocks” models of brain function: DNNs are grounded in sensory data\, can be trained to perform complex tasks in a distributed fashion\, are fully configurable/accessible to the experimenter\, and can be mapped to brain function across various levels of explanation. This has led to a fruitful research cycle in which biological aspects are integrated into network design\, and the corresponding networks are then tested for their ability to predict neural and behavioural data. This talk will present this emerging approach\, which we call neuroconnectionism\, as a cohesive large-scale research programme centered around ANNs as a computational language for expressing falsifiable theories about brain computation. As a case study\, I will focus on a collaborative effort in which we test the ability of large-language models (LLMs) to provide a good representational format for modelling human visual responses to natural scenes. By running tightly controlled model comparisons\, we demonstrate that recurrent neural networks\, trained to map from pixels to semantic LLM embedding\, provide the current best account of a large-scale\, 7T fMRI dataset (NSD)\, outperforming other supervised as well as unsupervised ANN models. These findings point towards the view that vision may not be optimised for visual categorisation alone\, but instead maps from retinal input into a high-dimensional semantic format that can be captured by contextual learning in language.\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Pietro Jeng on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-tim-kietzmann-university-of-osnabruck-large-language-models-offer-a-rich-representational-format-for-understanding-the-transformation-of-visual-information-in-the-human-bra/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
END:VCALENDAR