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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230119T160000
DTEND;TZID=Europe/Berlin:20230119T173000
DTSTAMP:20260409T133452
CREATED:20230102T111439Z
LAST-MODIFIED:20240813T101638Z
UID:13961-1674144000-1674149400@www.scienceofintelligence.de
SUMMARY:Ingmar Posner (University of Oxford)\, "Learning to Perceive and to Act - Disentangling Tales from (Structured) Latent Space"
DESCRIPTION:Abstract:\nUnsupervised learning is experiencing a renaissance. Driven by an abundance of unlabelled data and the advent of deep generative models\, machines are now able to synthesise complex images\, videos and sounds. In robotics\, one of the most promising features of these models – the ability to learn structured latent spaces – is gradually gaining traction. The ability of a deep generative model to disentangle semantic information into individual latent-space dimensions seems naturally suited to state-space estimation. Combining this information with generative world-models\, models which are able to predict the likely sequence of future states given an initial observation\, is widely recognised to be a promising research direction with applications in perception\, planning and control. Yet\, to date\, designing generative models capable of decomposing and synthesising scenes based on higher-level concepts such as objects remains elusive in all but simple cases. In this talk I will motivate and describe our recent work using deep generative models for unsupervised object-centric scene inference and generation. Furthermore\, I will make the case that exploiting correlations encoded in latent space\, and learnt through experience\, lead to a powerful and intuitive way to disentangle and manipulate task-relevant factors of variation. I will show that this not only casts a novel light on affordance learning\, but also that the same framework is capable of generating plans executable on complex real-world robot platforms. \nPhoto courtesy by Ingmar Posner. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-ingmar-posner-university-of-oxford-learning-to-perceive-and-to-act-disentangling-tales-from-structured-latent-space/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230105T160000
DTEND;TZID=Europe/Berlin:20230105T160000
DTSTAMP:20260409T133452
CREATED:20221215T134407Z
LAST-MODIFIED:20250603T130112Z
UID:13676-1672934400-1672934400@www.scienceofintelligence.de
SUMMARY:Peter Neri (Laboratoire Des Systèmes Perceptifs\, CNRS\, Paris)\, “The Unreasonable Recalcitrance of Human Vision to Theoretical Domestication”
DESCRIPTION:Abstract: \nWe can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference\, or an assembly of biological components not built for achieving statistical optimality. The former approach is attractive thanks to its elegance and potentially wide applicability\, however the basic facts of human pattern vision do not support it. Instead\, they indicate that the idiosyncratic behaviour produced by visual cortex is largely dictated by its hardware components. The output of these components can be steered towards optimality by our cognitive apparatus\, but only to a marginal extent. We conclude that current theories of visually-guided behaviour are at best inadequate\, and we turn to neural networks in an attempt to establish whether the idiosyncratic character of human vision may be learnt from a larger repertoire of functional constraints\, such as the statistics of the natural environment. We challenge deep convolutional networks with the same stimuli/tasks used with human observers and apply equivalent characterization of the stimulus–response coupling. For shallow depth of behavioural characterization\, some variants of network-architecture/training-protocol produce human-like trends; however\, more articulate empirical descriptors expose glaring discrepancies. Our results urge caution in assessing whether neural networks do or do not capture human behavior: ultimately\, our ability to assess ‘’success’’ in this area can only be as good as afforded by the depth of behavioral characterization against which the network is evaluated. More generally\, our results provide a compelling demonstration of how far we still are from securing an adequate computational account of even the most basic operations carried out by human vision. \nPhoto by Mathew Schwartz on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-peter-neri-laboratoire-des-systemes-perceptifs-cnrs-paris-the-unreasonable-recalcitrance-of-human-vision-to-theoretical-domestication/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T160000
DTEND;TZID=Europe/Berlin:20221124T173000
DTSTAMP:20260409T133452
CREATED:20220926T103901Z
LAST-MODIFIED:20240813T101918Z
UID:13096-1669305600-1669311000@www.scienceofintelligence.de
SUMMARY:Jan De Houwer (Ghent University)\, "Learning in Individual Organisms\, Genes\, Machines\, and Groups: A New Way of Defining and Relating Learning in Different Systems"
DESCRIPTION:Abstract:\nLearning is a central concept in many scientific disciplines. Communication about research on learning is\, however\, hampered by the fact that different researchers define learning in different ways. In this talk\, we introduce the extended functional definition of learning that can be used across scientific disciplines. We provide examples of how the definition can be applied to individual organisms\, genes\, machines\, and groups. The extended functional definition (a) reveals a heuristic framework for research that can be applied across scientific disciplines\, (b) allows researchers to engage in intersystem analyses that relate the behavior and learning of different systems\, and (c) clarifies how learning differs from other phenomena such as (changes in) behavior\, damaging systems\, and programming systems. \nPhoto by DeepMind on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-with-jan-de-houwer-learning-in-individual-organisms-genes-machines-and-groups-a-new-way-of-defining-and-relating-learning-in-different-systems/
LOCATION:MAR 2.057
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20220714T160000
DTEND;TZID=Europe/Berlin:20220714T173000
DTSTAMP:20260409T133452
CREATED:20220523T085120Z
LAST-MODIFIED:20250603T130312Z
UID:12100-1657814400-1657819800@www.scienceofintelligence.de
SUMMARY:Daniel M. Wolpert (Columbia University)\, “Contextual Inference Underlies the Learning of Sensorimotor Repertoires”
DESCRIPTION:Abstract:\nHumans spend a lifetime learning\, storing and refining a repertoire of motor memories. However\, it is unknown what principle underlies the way our continuous stream of sensorimotor experience is segmented into separate memories and how we adapt and use this growing repertoire. Here we develop a principled theory of motor learning based on the key insight that memory creation\, updating\, and expression are all controlled by a single computation – contextual inference. Unlike dominant theories of single-context learning\, our repertoire-learning model accounts for key features of motor learning that had no unified explanation and predicts novel phenomena\, which we confirm experimentally. These results suggest that contextual inference is the key principle underlying how a diverse set of experiences is reflected in motor behavior. \nThis event will take place on Zoom. \n  \nPhoto by afiq fatah on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/distinguish-speaker-series-with-daniel-m-wolpert/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20211209T160000
DTEND;TZID=Europe/Berlin:20211209T173000
DTSTAMP:20260409T133452
CREATED:20211116T144022Z
LAST-MODIFIED:20240813T095314Z
UID:11003-1639065600-1639071000@www.scienceofintelligence.de
SUMMARY:POSTPONED - Distinguished Speaker Series Talk\, Iain Couzin (University of Konstanz)
DESCRIPTION:Postponed to a later date (to be assessed) \nMore info coming soon! \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-talk-iain-cousin-university-of-konstanz/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20211028T160000
DTEND;TZID=Europe/Berlin:20211028T173000
DTSTAMP:20260409T133452
CREATED:20210908T113520Z
LAST-MODIFIED:20240813T093828Z
UID:10612-1635436800-1635442200@www.scienceofintelligence.de
SUMMARY:Cameron Buckner (Univ. of Houston)\, Imagination and the Prospects for Empiricist Artificial Intelligence
DESCRIPTION:Abstract: In current debates over deep-neural-network-based AI\, deep learning researchers have adopted the mantle of philosophical empiricism and associationism\, and its critics have taken up the side of philosophical rationalism and nativism.  These rationalist critics\, however\, often interpret associationism and empiricism in a way which is too caricatured to fit the views of any significant thinker in the empiricist tradition.  In particular\, most empiricists were faculty theorists; while they generally eschewed innate knowledge\, they appealed to a variety of domain-general innate faculties like memory\, imagination\, and attention to explain how the mind abstracts knowledge from experience.  This dynamic is vividly illustrated in a centuries-displaced debate between David Hume and Jerry Fodor over the role of imagination in cognitive architecture.  Fodor famously claimed that the ability to synthesize novel ideas and create new compositional representations is required for cognition.  Fodor applauds Hume for agreeing on these points\, but criticizes Hume’s use of the imagination to discharge these burdens.  Fodor claims that such an appeal for an associationist is “cheating”\, and notes that Hume never explains how the empiricist imagination actually works\, merely assigning it a variety of essential functions to perform “as if by magic”. \nMore recently\, deep learning researchers have claimed to create generative deep neural network models that perform one or more of the roles ascribed to the imagination by cognitive psychology and neuroscience.  In this talk\, I canvass these models and their achievements (especially Generative Adversarial Networks\, Variational Autoencoders\, and Generative Transformers) to arbitrate this dispute between Humean empiricism and Fodorian rationalism.  Of particular interest will be various methods of latent space vector interpolation which appear to allow these models to create novel compositional representations\, whether these methods still count as associationist in nature\, and whether the purportedly crucial distinction between interpolation and extrapolation remains viable in the higher-order dimensional spaces over which these models operate. \nClick here for Cameron Buckner’s Bio. \nThe Zoom Link will be sent the day before the lecture.
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-cameron-buckner-university-of-houston/
LOCATION:On Zoom
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20210624T160000
DTEND;TZID=Europe/Berlin:20210624T173000
DTSTAMP:20260409T133452
CREATED:20210607T113648Z
LAST-MODIFIED:20250604T095548Z
UID:10284-1624550400-1624555800@www.scienceofintelligence.de
SUMMARY:Kou Murayama (Universität Tübingen)\, “A Reward-Learning Framework of Knowledge Acquisition: How We Can Integrate the Concepts of Curiosity\, Interest\, and Intrinsic-Extrinsic Rewards.”
DESCRIPTION:Recent years have seen a considerable surge of research on interest-based engagement\, examining how and why people are engaged in activities without relying on extrinsic rewards. However\, the field of inquiry has been somewhat segregated into three different research traditions which have been developed relatively independently — research on curiosity\, interest\, and trait curiosity/interest. The current talk sets out an integrative perspective; the reward-learning framework of knowledge acquisition. This conceptual framework takes on the basic premise of existing reward-learning models of information seeking: that knowledge acquisition serves as an inherent reward\, which reinforces people’s information-seeking behavior through a reward-learning process. However\, the framework reveals how the knowledge-acquisition process is sustained and boosted over a long period of time in real-life settings\, allowing us to integrate the different research traditions within reward-learning models. The framework also characterizes the knowledge-acquisition process with four distinct features that are not present in the reward-learning process with extrinsic rewards — (1) cumulativeness\, (2) selectivity\, (3) vulnerability\, and (4) under-appreciation. The talk describes some evidence from our lab supporting these claims. \nHosted by Rebecca Lazarides \nSpeaker website: https://koumurayama.com/people.php \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distingushed-speaker-series-kou-murayama-universitat-tubingen-hosted-by-rebecca-lazarides/
LOCATION:On Zoom
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20210527T160000
DTEND;TZID=Europe/Berlin:20210527T180000
DTSTAMP:20260409T133452
CREATED:20210426T083427Z
LAST-MODIFIED:20250604T095629Z
UID:10091-1622131200-1622138400@www.scienceofintelligence.de
SUMMARY:Antje Nuthmann (University of Kiel)\, “Real-World Scene Perception and Search From Foveal to Peripheral Vision”
DESCRIPTION:It is a commonly held assumption that the fovea is where the interesting action occurs. To scrutinize this assumption\, we conducted a series of experiments that addressed the following question: How important are the different regions of the visual field for gaze guidance in everyday visual-cognitive tasks? Following on from classic findings for sentence reading\, I will present key results from various experiments in which observers had to search for a target within static or dynamic images of real-world scenes. Each scene image contained exactly one target\, which was either contextually relevant (e.g.\, “Look for the apple”) or not (e.g.\, “Look for the ‘T’”). Gaze-contingent scotomas were used to selectively deny information processing in the fovea\, parafovea\, or periphery. Overall\, the results suggest that foveal vision is less important and peripheral vision is more important for scene perception and search than previously thought. The importance of foveal vision was found to depend on the specific requirements of the task. Finally\, when observers searched for a static target in dynamic scenes\, only their very first saccade was guided by task-irrelevant motion in extrafoveal and peripheral vision.\n\n(Photo © Jürgen Haacks\, Uni Kiel)\nThe Zoom Link will be sent the day before the lecture.
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-antje-nuthmann-university-of-kiel-real-world-scene-perception-and-search-from-foveal-to-peripheral-vision/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20210429T160000
DTEND;TZID=Europe/Berlin:20210429T180000
DTSTAMP:20260409T133452
CREATED:20210126T081803Z
LAST-MODIFIED:20240813T092630Z
UID:9574-1619712000-1619719200@www.scienceofintelligence.de
SUMMARY:Peter Dayan\, (Max Planck Institute for Biological Cybernetics)\, "Peril\, Prudence and Planning as Risk\, Avoidance and Worry"
DESCRIPTION:Speaker: Peter Dayan\, Max Planck Institute for Biological Cybernetics\, https://www.mpg.de/12309357/biologische-kybernetik-dayan\nHosted by Henning Sprekeler; moderated by Robert Tjarko Lange \nPeril\, Prudence and Planning as Risk\, Avoidance and Worry\nRisk occupies a central role in both the theory and practice of decision-making. Although it is deeply implicated in many conditions involving dysfunctional behavior and thought\, modern theoretical approaches to understanding and mitigating risk in either one-shot or sequential settings\, which are derived largely from finance and economics\, have yet to permeate fully the fields of neural reinforcement learning and computational psychiatry. I will discuss the use of dynamic and static versions of one prominent approach\, namely conditional value-at-risk\, to examine both the nature of risk avoidant choices\, encompassing such things as justified gambler’s fallacies\, and the optimal planning that can lead to consideration of such choices\, with implications for offline\, ruminative\, thinking. This is joint work with Chris Gagne.\n \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-peter-dayan/
LOCATION:On Zoom
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20201217T163000
DTEND;TZID=Europe/Berlin:20201217T183000
DTSTAMP:20260409T133452
CREATED:20200309T121316Z
LAST-MODIFIED:20240417T125500Z
UID:7256-1608222600-1608229800@www.scienceofintelligence.de
SUMMARY:Patricia Churchland (University of California\, San Diego)\, The Neurobiological Platform for Moral Intuitions
DESCRIPTION:ABSTRACT: Self-preservation is embodied in our brain’s circuitry: we seek food when hungry\, warmth when cold\, and mates when lusty. In the evolution of the mammalian brain\, circuitry for regulating one’s own survival and well-being was modified. For sociality\, the important result was that the ambit of me extends to include others — me-and-mine. Offspring\, mates\, and kin came to be embraced in the sphere of  me-ness; we nurture them\, fight off threats to them\, keep them warm and safe. The brain knows these others are not me\, but if I am attached to them\, their plight fires-up caring circuitry\, motivating other-care that resembles self-care. In some species\, including humans\, seeing to the well-being of others may extend\, though less intensely\, to include friends\, business contacts or even strangers\, in an ever-widening circle. Oxytocin\, an ancient body-and-brain molecule\, is at the hub of the intricate neural adaptations sustaining mammalian sociality. Not acting alone\, oxytocin works with other hormones and neurotransmitters and structural adaptations. Among its many roles\, oxytocin decreases the stress response\, making possible the friendly\, trusting interactions typical of life in social mammals. I can let my guard down when I know I am among trusted family and friends. \n  \nBIO: For decades\, Patricia Churchland has contributed to the fields of philosophy of neuroscience\, philosophy of the mind and neuroethics. Her research has centered on the interface between neuroscience and philosophy with a current focus on the association of morality and the social brain. A Professor Emeritus of Philosophy at the University of California\, San Diego and Adjunct Professor at the Salk Institute\, Pat holds degrees from Oxford University\, the University of Pittsburg and the University of British Columbia. She has been awarded the MacArthur Prize\, The Rossi Prize for Neuroscience and the Prose Prize for Science. She has authored multiple pioneering books\, her most recent being Touching a Nerve. She has served as President of the American Philosophical Association and the Society for Philosophy and Psychology. Pat lives in Solana Beach\, California\, with her husband Paul\, a neurophilosopher\, and their labradoodle Millie. They have two children\, Anne and Mark\, both neuroscientists. Read more about her work on her website.\nPatricia Churchland is also a member of SCIoI’s Scientific Advisory Board.
URL:https://www.scienceofintelligence.de/event/distinguished-people-series-talia-konkle-host-martin-rolfs/
LOCATION:On ZOOM (Contact us for Link)
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20201203T160000
DTEND;TZID=Europe/Berlin:20201203T180000
DTSTAMP:20260409T133452
CREATED:20200824T130544Z
LAST-MODIFIED:20240813T092247Z
UID:8554-1607011200-1607018400@www.scienceofintelligence.de
SUMMARY:Naomi Leonard\, Princeton University (hosted by Jörg Raisch): Opinion Dynamics with Tunable Sensitivity:  Consensus\, Dissensus\, and Cascades
DESCRIPTION:I will present a model of continuous-time opinion dynamics for an arbitrary number of agents that communicate over a network and form real-valued opinions about an arbitrary number of options.  The model generalizes linear and nonlinear models in the literature. Drawing from biology\, physics\, and social psychology\, we introduce an attention parameter to modulate social influence and a saturation function to bound inter-agent and intra-agent opinion exchanges.  This yields simply parameterized dynamics that exhibit the range of opinion formation behaviors predicted by model-independent bifurcation theory but not exhibited by linear models or existing nonlinear models. Behaviors include reliable formation of consensus and dissensus\, even in homogeneous networks\, and opinion cascades. The opinion dynamics also display ultra-sensitivity to inputs\, robustness to disturbance\, and flexible transitions between consensus and dissensus. Augmenting the opinion dynamics with feedback dynamics for the attention parameter results in tunable thresholds that govern sensitivity\, robustness\, and flexibility.  The model provides new means for systematic study of dynamics on natural and engineered networks\, from information spread and political polarization to collective decision making and dynamic task allocation. This is joint work with Alessio Franci (UNAM\, Mexico) and Anastasia Bizyaeva (Princeton). \nNaomi Ehrich Leonard is a control theorist whose work involves analysis and design of feedback and interconnection in complex\, dynamical systems.  She uses mathematical models and methods to study mechanisms of collective motion and collective decision making for multi-agent systems in nature (analysis of animal and human groups) and in engineering (design of autonomous robotic teams and mobile sensor networks).  She has applied her work to the collective dynamics of killifish\, starlings\, honeybees\, zebras\, and desert harvester ants\, as well as to rule-based improvisational dance.  She led a multidisciplinary ocean sensing project with a month-long deployment of an automated\, adaptive network of underwater robotic vehicles in Monterey Bay\, CA.  Leonard is the Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering and associated faculty member of the Program in Applied and Computational Mathematics at Princeton University.  She is a MacArthur Fellow\, a Fellow of the American Academy of Arts and Sciences\, IEEE\, SIAM\, ASME\, and IFAC. Visit her website here. \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-naomi-leonard-princeton-university-hosted-by-jorg-raisch/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20201126T160000
DTEND;TZID=Europe/Berlin:20201126T180000
DTSTAMP:20260409T133452
CREATED:20200824T130327Z
LAST-MODIFIED:20250604T095807Z
UID:8550-1606406400-1606413600@www.scienceofintelligence.de
SUMMARY:Michele Rucci\, University of Rochester (Hosted by Marianne Maertens): Seeing by Moving: The Indissoluble Bond Between Perception and Action
DESCRIPTION:Seeing by moving: the indissoluble bond between perception and action \nEstablishing a representation of space is a major goal of sensory systems.  Spatial information\, however\, is not always explicit in the incoming sensory signals. In most modalities it needs to be actively extracted from cues embedded in the temporal flow of receptor activation. Vision\, on the other hand\, starts with a sophisticated optical imaging system that explicitly preserves spatial information on the retina. This may lead to the assumption that vision is predominantly a passive spatial process: all that is needed is to transmit the retinal image to the cortex\, like uploading a digital photograph\, to establish a spatial map of the world. However\, this deceptively simple analogy is inconsistent with theoretical models and experiments that study visual processing in the context of normal motor behavior. I will argue that\, as with other senses\, vision relies heavily on sensorimotor strategies to extract and represent spatial information in the temporal domain. \nBio:\n \nMichele Rucci investigates the computational and biological mechanisms underlying visual perception following an ecological approach that studies vision in conjunction with motor behavior – in particular eye movements and characteristics of natural environments. In his Active Perception Laboratory\, his work has led to multiple findings on the roles of eye movements in the encoding of visual information and the establishment of spatial representations\, leading to the development of new tools for experimental studies and robots directly controlled by models of neural pathways. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-michele-rucci-hosted-by-marianne-maertens/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20201029T110000
DTEND;TZID=Europe/Berlin:20201029T123000
DTSTAMP:20260409T133452
CREATED:20200824T125720Z
LAST-MODIFIED:20250604T095856Z
UID:8547-1603969200-1603974600@www.scienceofintelligence.de
SUMMARY:Giovanni Pezzulo\, ISTC-CNR Rome (Host: Verena Hafner): Human Sensorimotor Communication During Human Joint Action: Experimental and Computational Perspectives
DESCRIPTION:Giovanni Pezzulo is a researcher at the Institute of Cognitive Sciences and Technologies\, National Research Council in Rome\, Italy. His research centers on the neuronal and computational mechanisms of predictive processing\, goal-directed behaviour\, and the sensorimotor foundations of higher cognition. \nHuman sensorimotor communication during human joint action: experimental and computational perspectives \nDuring online social interactions\, humans engage in various forms of non-linguistic communication. I will discuss recent research in my lab and others about sensorimotor communication (SCM): the study of the subtle communicative signals embedded within our everyday pragmatic actions. SMC is ubiquitous during realistic social interactions. For example\, soccer players often carve their body movements in ways that are informative for their teammates or deceptive for their adversaries. Furthermore\, we have many ways to perform the same goal-directed action – say\, offer a glass of wine – and small kinematic differences can make the same action rude\, polite or snobbish\, thus potentially unveiling our hidden intentions. I will present some human-human experiments on SMC and discuss them in the context of a theoretical and computational model that we have been developing\, and which considers both the costs and benefits of SMC (e.g.\, in terms of increased interaction success). More broadly\, I will discuss our current understanding of the computational (and\, in part\, neural) mechanisms underlying social interaction at large\, including e.g.\, action observation\, prediction and planning mechanisms. \n— \nRe background material: \nFor a good introduction https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0079876Photo by Uriel SC on Unsplash \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-giovanni-pezzulo-hosted-by-verena-hafner/
CATEGORIES:Distinguished Speaker Series
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DTSTART;TZID=Europe/Berlin:20201022T160000
DTEND;TZID=Europe/Berlin:20201022T173000
DTSTAMP:20260409T133452
CREATED:20200824T124927Z
LAST-MODIFIED:20250604T100024Z
UID:8544-1603382400-1603387800@www.scienceofintelligence.de
SUMMARY:Guy Theraulaz\, (CNRS\, Toulouse\, France. Host: Pawel Romanczuk): Ethological Analysis and Computational Modeling of Social Interactions in Schooling Fish
DESCRIPTION:Abstract: Swarms of insects\, schools of fish and flocks of birds display an impressive variety of collective movement patterns that emerge from interactions among group members. These puzzling phenomena raise a variety of questions about the interaction rules that govern the coordination of individuals’ motion and the emergence of large-scale patterns. While numerous models have been proposed\, there is still a strong need for detailed experimental studies to foster the biological understanding of such collective motion phenomena. I will first describe the methods that we have developed in the recent years to characterize social interactions between individuals involved in the coordination of swimming in Rummy-nose tetra (Hemigrammus rhodostomus) from data gathered at the individual scale. This species of tropical fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive\, straight decelerations. Our results show that both attraction and alignment behaviors control the reaction of fish to a neighbor. Then I will present how these results can be used to build a model of spontaneous burst-and-coast swimming and social interactions of fish\, with all parameters being estimated or directly measured from experiments. This model shows that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observed in groups of five fish. Increasing the number of interacting neighbors does not significantly improve the simulation results. Remarkably\, we find that groups remain cohesive and polarized even when each agent only interacts with only one of its neighbors: the one that has the strongest contribution to the heading variation of the focal agent. Finally\, I will present a swarm robotic platform with which we investigate the impact of collision avoidance based on speed control on the group behavior. This platform combines the implementation of the fish behavioral model and an engineering-minded control system to deal with real-world physical constraints. Remarkably\, and as already observed in the model simulations\, even when robots only interact with their most influential neighbor\, our results show that the group remains highly cohesive and polarized while reproducing the behavioral patterns observed in groups of fish in experimental conditions. Overall\, our results suggest that fish have to acquire only a minimal amount of information about their environment to coordinate their movements when swimming in groups.\n  \nShort bio: Guy Theraulaz is a senior research fellow at the National Center for Scientific Research (CNRS) and an expert in the study of collective animal behaviors. He is also a researcher in the field of swarm intelligence\, primarily studying social insects but also distributed algorithms\, e.g. for collective robotics\, directly inspired by nature. His research focuses on the understanding of a broad spectrum of collective behaviors in animal societies by quantifying and then modeling the individual level behaviors and interactions\, thereby elucidating the mechanisms generating the emergent\, group-level properties. He has published many papers on nest construction in ant\, wasp and termite colonies\, collective decision-making in ants and cockroaches\, collective motion in fish schools and human crowds and collective estimation in human groups. He has also coauthored five books\, among which Swarm Intelligence: From Natural to Artificial Systems (Oxford University Press\, 1999) and Self-organization in biological systems (Princeton University Press\, 2001) that are now considered as reference textbooks. In 2019\, he has been appointed visiting chair professor in Collective Behavior\, at the Indian Institute of Science in Bangalore by the Infosys Foundation.\n  \nWebpage: http://crca.cbi-toulouse.fr/en/guytheraulaz/\n \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-guy-theraulazhost-pawel-romanczuk/
CATEGORIES:Distinguished Speaker Series
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DTSTART;TZID=Europe/Berlin:20200625T160000
DTEND;TZID=Europe/Berlin:20200625T180000
DTSTAMP:20260409T133452
CREATED:20200309T121608Z
LAST-MODIFIED:20250604T100103Z
UID:7262-1593100800-1593108000@www.scienceofintelligence.de
SUMMARY:Jacqueline Gottlieb (Hosted by Martin Rolfs): Curiosity and Information Demand: How We Can Study Them and Why We Should Care
DESCRIPTION:Curiosity and information demand: how we can study them and why we should care \nA rapidly growing literature has recently emphasized the importance of our sense-making instincts\, including complex investigative behaviors such as curiosity\, for behavior and brain function. While much of this literature has focused on simple forms of decision making\, we explored its significance for attention allocation. To make adaptive decisions in realistic multi-dimensional environments\, animals must infer the relevant features and afford them priority for the control of learning and actions. Prioritizing sources of information is the role of executive control and attention\, but its neural mechanisms are poorly understood. I will review studies of information demand suggesting that the fronto-parietal network encodes both optimal and non-optimal mechanisms for attentional prioritization. Converging evidence shows that parietal neurons encode prior uncertainty and likelihood\, two quantities required for Bayesian prioritization that maximizes the reduction in uncertainty. However\, the neurons also encode priority based on hedonic stimulus-reward associations\, in ways that seem non-optimal and interfere with the reduction of uncertainty. Continued studies of information demand will shed light on the vital question of how animals make complex decisions in realistic settings – specifically\, how they endogenously assign salience or priority to competing sources of information that subsequently control learning and actions. \nJacqueline Gottlieb\, Department of Neuroscience\, The Kavli Institute for Brain Science\, The Zuckerman Institute for Mind Brain and Behavior\, Columbia University\, New York\, NY\, 10032\, www.gottlieblab.com \nThe Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions) \n  \n(Photo by JR Korpa on Unsplash)
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-jacqueline-gottlieb/
LOCATION:On ZOOM (Contact us for Link)
CATEGORIES:Distinguished Speaker Series
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