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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240411T100000
DTEND;TZID=Europe/Berlin:20240411T110000
DTSTAMP:20260615T142621
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:20260615T142621
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2024/04/Jacek-Wiland-1024x1024-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240328T100000
DTEND;TZID=Europe/Berlin:20240328T113000
DTSTAMP:20260615T142621
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:20260615T142621
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:20260615T142621
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:20260615T142621
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
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240201T100000
DTEND;TZID=Europe/Berlin:20240201T110000
DTSTAMP:20260615T142621
CREATED:20231113T091900Z
LAST-MODIFIED:20250603T125206Z
UID:17049-1706781600-1706785200@www.scienceofintelligence.de
SUMMARY:Stefan Leutgeb\, “Hippocampal Computations in Support of Spatial Navigation and Working Memory”
DESCRIPTION:Stefan Leutgeb is Professor of Neurobiology at University of California San Diego. Currently a fellow of the Wissenschaftskolleg zu Berlin with his research on neural computations in real brains and in artificial systems. More details to follow.\n\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Alina Grubnyak on Unsplash. \n  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-stefan-leutgeb-hippocampal-computations-in-support-of-spatial-navigation-and-working-memory/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/11/alina-grubnyak-tEVGmMaPFXk-unsplash.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240125T100000
DTEND;TZID=Europe/Berlin:20240125T110000
DTSTAMP:20260615T142621
CREATED:20240108T132410Z
LAST-MODIFIED:20240415T104537Z
UID:18010-1706176800-1706180400@www.scienceofintelligence.de
SUMMARY:Oren Forkosh (The Hebrew University of Jerusalem)\, "Behavior\, Personality\, and Affective States of Freely Behaving Groups of Mice and Other Animals"
DESCRIPTION:Behavior\, Personality\, and Affective States of Freely Behaving Groups of Mice and Other Animals\nIn recent years\, the study of animal behavior in neuroscience has seen a significant shift towards more naturalistic and less intrusive methods. It is under these conditions that the true spectrum of animal behavior can be exhibited\, free from the artificial constraints and stressful conditions often imposed by traditional laboratory settings. In this talk\, I will discuss the interplay between behavior\, personality\, and affective states as measured in our “social boxes”; These systems allow for the continuous and unattended tracking of groups of mice over extended periods and can automatically recognize and catalog over 100 distinct behaviors. A four-day experiment\, for example\, can potentially replace a myriad of classical tests typically used in neuroscience. Our system can also discern and record a ‘behavioral fingerprint’ for each mouse. These fingerprints reveal consistent traits—personalities—that are not only distinct between individuals but also persist over time. In addition\, by examining the interplay between behavior and personality across multiple timescales – from seconds to days – we can gain insights into the affective states of these animals. Finally\, expanding our research to other species\, including bats\, cows\, and even humans\, allows us to develop a general understanding of behavior and personality. This comparative strategy holds promise for developing a ‘universal translator’ of behavioral and personality patterns\, paving the way for new comparative studies. These insights into the personalities and emotions of both humans and animals have the potential to significantly enhance our knowledge of the neurobiological underpinnings of behavior. \n—Oren Forkosh is a PI at the Lab for Computational Neuroscience- Behavior\, Personality and Cognition at the Hebrew University of Jerusalem. The Forkosh lab uses machine-learning to understand personality\, behaviour\, hierarchy\, communication\, social learning\, and much more\, in order to make the world happier for animals and people alike. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-oren-forkosh-the-hebrew-university-of-jerusalem-behavior-personality-and-affective-states-of-freely-behaving-groups-of-mice-and-other-animals/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20240118T100000
DTEND;TZID=Europe/Berlin:20240118T110000
DTSTAMP:20260615T142621
CREATED:20231220T123724Z
LAST-MODIFIED:20250603T125238Z
UID:18004-1705572000-1705575600@www.scienceofintelligence.de
SUMMARY:Asieh Daneshi (Science of Intelligence)\, “Behavioral Contagion in Human and Artificial Multi-Agent Systems”
DESCRIPTION:In this talk\, Asieh will explore the dynamics of decision-making and risk-taking within social contexts and how everyday decisions\, often laden with potential negative outcomes\, are influenced not only by individual judgment but significantly by the surrounding social environment. Her research employs the “Balloon Analogue Risk-Taking” experiment in a controlled setting applying VR-technology in order to investigate the impact of dynamic social interactions on individual risk assessment. Various aspects\, such as the effect of peers on risk perception\, group dynamics in decision-making\, and the influence of social norms on risk-taking behaviors are part of her study. \nBy observing how individuals in a group adapt their decisions based on others’ actions and outcomes\, she aims to understand the balancing act between individual decision-making and group conformity. This research explores decision-making in a constantly changing social environment\, offering new insights into how group dynamics can lead to either more risk-taking or conservative behaviors. The findings promise to enhance our understanding of the complex interplay between personal psychology and group influence. \n\n\n\n\n\nThis talk will take place in person at SCIoI. \n  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-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:20231214T100000
DTEND;TZID=Europe/Berlin:20231214T110000
DTSTAMP:20260615T142621
CREATED:20231113T092531Z
LAST-MODIFIED:20240813T102801Z
UID:17050-1702548000-1702551600@www.scienceofintelligence.de
SUMMARY:Aravind Battaje and Vito Mengers\, "Principles at Play: What is Intelligence?"
DESCRIPTION:What is intelligence? We delve into the collaborative efforts at SCIoI\, where we aim to understand intelligence through the identification of commonalities. Inspired by ongoing research and historical parallels\, we present candidate principles\, inviting the audience to contribute insights and discuss their alignment with ongoing projects. This talk marks a step towards refining our understanding of intelligence\, emphasizing the pivotal role principles play in shaping our collective reflections and influencing future research trajectories.\n\n\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-vito-mengers-project-35-differentiable-interconnected-recursive-estimation-as-a-principle-of-intelligence/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231130T100000
DTEND;TZID=Europe/Berlin:20231130T110000
DTSTAMP:20260615T142621
CREATED:20231020T092645Z
LAST-MODIFIED:20250603T125309Z
UID:17048-1701338400-1701342000@www.scienceofintelligence.de
SUMMARY:Eva Wiese (TU Berlin)\, “Social Perception and Attention in Human-Robot Interaction: Bottom-Up and Top-Down Influences”
DESCRIPTION:Eva Wiese is the professor for Cognitive Psychology and Ergonomics at TU Berlin. More details to follow.\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Possessed Photography on Unsplash\,  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-eva-wiese/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231109T100000
DTEND;TZID=Europe/Berlin:20231109T110000
DTSTAMP:20260615T142621
CREATED:20231004T125227Z
LAST-MODIFIED:20250603T125349Z
UID:16860-1699524000-1699527600@www.scienceofintelligence.de
SUMMARY:Daniela Vallentin (MPI for Biological Intelligence)\, “Neural Mechanisms of Vocal Learning and Production in Songbirds”
DESCRIPTION:Daniela Vallentin is a neuroscientist and currently the Lise Meitner Reseach Group Leader at the Max Planck Institute for Biological Intelligence\, heading the ‘Neural Circuits for Vocal Communication’ Group whose objective is to explore the neural circuits driving skilled motor learning and orchestrating the coordination of precise movements by working with songbirds. Due to the homology of brain structures in birds and mammals\, studying the neural mechanisms of vocal learning and coordination in songbirds has the potential to reveal general principles of motor circuits in other animals\, including humans.\n\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Joshua J. Cotten on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-daniela-vallentin-mpi-for-biological-intelligence-neural-mechanisms-of-vocal-learning-and-production-in-songbirds/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231102T100000
DTEND;TZID=Europe/Berlin:20231102T110000
DTSTAMP:20260615T142621
CREATED:20230918T084845Z
LAST-MODIFIED:20250603T125402Z
UID:16719-1698919200-1698922800@www.scienceofintelligence.de
SUMMARY:Jonas Frenkel and Uroš Petković (Science of Intelligence)\, “Social Responsiveness and Its Effects on Learning in Human-Human and Human-Robot Interaction”
DESCRIPTION:More details to follow.\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Katja Anokhina on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-project-31-social-responsiveness-and-its-effects-on-learning-in-human-human-and-human-robot-interaction/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231026T100000
DTEND;TZID=Europe/Berlin:20231026T110000
DTSTAMP:20260615T142621
CREATED:20230927T091538Z
LAST-MODIFIED:20250603T125413Z
UID:16730-1698314400-1698318000@www.scienceofintelligence.de
SUMMARY:Svetlana Levit\, “Analyzing Human Physical Reasoning and Strategy Exploration on Physical Puzzles”
DESCRIPTION:More details to follow.\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Markus Spiske on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-svetlana-levit-project-30/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231019T100000
DTEND;TZID=Europe/Berlin:20231019T110000
DTSTAMP:20260615T142621
CREATED:20230918T084300Z
LAST-MODIFIED:20240813T102952Z
UID:16715-1697709600-1697713200@www.scienceofintelligence.de
SUMMARY:Richard Schweitzer (Science of Intelligence)\, "Preregistration in Open Science: What\, why\, and how (a live tutorial)"
DESCRIPTION:Abstract: \nA tutorial on Open Science practices with a focus on pre-registration\, going through the process step-by-step\, including a live experimental data collection.\n\n\nThis talk will take place in person at SCIoI. \nPhoto by Markus Spiske on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-richard-schweitzer-preregistration-in-open-science-what-why-and-how-a-live-tutorial/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231005T100000
DTEND;TZID=Europe/Berlin:20231005T110000
DTSTAMP:20260615T142621
CREATED:20230515T104937Z
LAST-MODIFIED:20250603T125727Z
UID:15430-1696500000-1696503600@www.scienceofintelligence.de
SUMMARY:Conor Heins\, “Collective Behavior From Surprise Minimization”
DESCRIPTION:Abstract: \nCollective motion is a familiar sight in nature; groups of distinct\, self-propelled individuals appear to move as a coherent whole\, exhibiting a rich behavioral repertoire that ranges from directed movement to milling to disordered swarming. Biological collective motion is an emergent phenomenon that is the result of self-organization\, whereby macroscopic patterns arise from decentralized\, local interactions among constituent components (e.g.\, individual fish in a school). Preminent models of collective motion describe individuals in the group as self-propelled particles\, subject to a combination of self-generated motion and “social forces” that depend on the state of neighboring particles. Here we introduce a fundamentally new approach to modelling collective movement in animal groups based on active inference\, a cognitive framework that casts behavior as consequences of a single imperative: to minimize surprise. We demonstrate that many empirically-observed collective phenomena\, including cohesion\, milling and directed motion\, naturally emerge when considering individual behavior as the consequence of active Bayesian inference — this emerges without ever explicitly building behavioral rules or goals into individual agents. We show that active inference can naturally recover and generalize the classical notion of social forces in agent-based models of collective motion. By analyzing the parameter space of the belief-based model\, we reveal non-trivial relationships between the beliefs of individuals and group properties like collective polarization and the probability of occupying different behavioral regimes. We also explore how individual beliefs about uncertainty influence the accuracy of collective decision-making. Finally\, we show how\, in this framework\, agents can readily update their generative model over time\, resulting in groups that are collectively more sensitive to external fluctuations and encode information more robustly.\n\n\nThis talk will take place in person at SCIoI. \nPhoto kinldy provided by Shintaro Shiba. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-conor-heins-collective-behavior-from-surprise-minimization/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230720T100000
DTEND;TZID=Europe/Berlin:20230720T110000
DTSTAMP:20260615T142621
CREATED:20230605T103948Z
LAST-MODIFIED:20240813T103027Z
UID:15696-1689847200-1689850800@www.scienceofintelligence.de
SUMMARY:Lisa-Kristin Richter\, "Model Training for Facial Recognition of Raccoons"
DESCRIPTION:Machine learning tools have already been used to identify individual animals such as but not limited to pandas\, black bears\, cows and dogs. These tools can help to improve the quality of non-invasive wildlife monitoring and enhance the information on individual animal behaviour as well as on behaviour within social networks of the animals (Lynn 2019; Schofield et al. 2019). \nRaccoons (proctorloco) are considered an invasive species in Germany that has been introduced to many parts of the world outside of their native range in North America. \nIn order to train a model for facial recognition of raccoons\, we collected 7812 pictures of 133 individuals. After manual selection for quality focusing on sharpness\, image detail and light\, 111individuals with 4000 pictures remain in the dataset. The individuals were pictured in more than 10 different facilities and locations with different lights and angles. From this baseline dataset\, one data set using bounding boxes is created for training and one dataset using masks is also created for training. This is done to keep the influence of the background minimal. \nFinally\, this data is used to train different pre-trained deep learning models from Image Net\, namely ResNet50\, VGG19 and Mobile Net. While model training parameters like batch size\, number of epochs\, learning rate scheduler\, picture augmentation techniques and more are being varied. \nChallenges arise from the time and computer resources needed for training.Currently\, training is done via Google Colab\, which disconnects after a certain time. Furthermore\, input on dataset preprocessing\, model selection\, possible combination of models and variation in parameters would be very helpful. \nThis talk will take place in person at SCIoI. \nPhoto by Lukas Stoermer on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-lisa-kristin-richter/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230713T100000
DTEND;TZID=Europe/Berlin:20230713T110000
DTSTAMP:20260615T142621
CREATED:20230605T103302Z
LAST-MODIFIED:20240813T103032Z
UID:15693-1689242400-1689246000@www.scienceofintelligence.de
SUMMARY:Santiago Paternain\, "Safe Learning for Dynamical Systems and Control"
DESCRIPTION:Abstract: \nReinforcement learning has shown great success in controlling complex dynamical systems. However\, when training a policy\, most algorithms only consider a single objective function. While this may suffice in virtual domains\, physical systems must satisfy a set of operational constraints\, with safety being of crucial importance. It is natural to express these problems as constrained optimization problems since weighted combinations of different rewards are not guaranteed to find a solution that satisfies all the requirements. Furthermore\, these examples are not contrived\, and safety-constrained reinforcement learning is a vital area of research that needs to be tackled. \nAfter establishing the need to tackle safety-constrained reinforcement learning\, I will shift my focus to solving these generally non-convex problems. I will discuss different approaches that exploit duality theory to pave the way towards algorithms for general constrained reinforcement learning. In particular\, I will discuss that (i) despite their non-convexity these problems have zero duality gap\, (ii) a state-augmented approach that does not guarantee convergence to an optimal policy but\, it guarantees optimality and (iii) a safe policy-gradient theorem that allows us to consider constraints beyond time-averages. \nThis talk will take place in person at SCIoI. \n  \nPhoto by Jeswin Thomas on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-santiago-paternain/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230629T100000
DTEND;TZID=Europe/Berlin:20230629T110000
DTSTAMP:20260615T142621
CREATED:20230320T104739Z
LAST-MODIFIED:20240813T103037Z
UID:15010-1688032800-1688036400@www.scienceofintelligence.de
SUMMARY:Michael Taborsky\, "The Evolution of Social Behaviour"
DESCRIPTION:Abstract:\nThe social structure and behaviour of organisms is highly divergent. How can this stunning diversity in nature be explained? I will argue that a few key principles are responsible for the evolution of social behaviour\, with all its simple and complex manifestations. Organisms compete for resources. As survival and reproduction require resources and only fiction knows a land of milk and honey\, different individuals inevitably compete due to their own diverging fitness interests. To succeed in the competition for resources\, organisms may either “race” to be quicker than others\, “fight” for privileged access\, or “share” their efforts and gains. In this talk\, I attempt to show how the ecology and intrinsic attributes of organisms select for each of these strategies. My special emphasis will be on the evolution of cooperation\, with examples including a range of different taxa. Here the crucial question is how the conflict of fitness interests can be mediated to allow competitors for resources to unite and benefit from collective goal pursuit. \nThis talk will take place in person at SCIoI. \nPhoto by Torsten Dederichs on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-michael-taborsky-the-evolution-of-social-behaviour/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230622T100000
DTEND;TZID=Europe/Berlin:20230622T110000
DTSTAMP:20260615T142621
CREATED:20230320T104029Z
LAST-MODIFIED:20240813T103057Z
UID:15007-1687428000-1687431600@www.scienceofintelligence.de
SUMMARY:Mohsen Raoufi (Science of Intelligence)\, From State Estimation to Collective Estimation\, and from Individuality to Complexity in Swarm Robotic Systems
DESCRIPTION:Using swarm optimization algorithms as heuristic solutions in various engineering problems\, including the state estimation of nonlinear systems\, has been an inspiration to me for my SCIoI project. We started our project by studying the “Wisdom of Crowds” effect\, i.e. the notion that the average of many imperfect estimations\, under the right conditions\, can potentially yield a perfect estimation. However\, achieving an accurate estimation in a distributed manner requires individuals to finely balance many tradeoffs\, e.g. the exploration-exploitation trade-off. In addition to discussing a few of these tradeoffs in my talk\, I will demonstrate how the interaction of agents leads to more complex behavior\, particularly when the connectivity of the communication network is limited. For instance\, this limitation results in the emergence of “echo-chambers” in the collectives. \nIn the second part\, I will talk about the inter-individual variations we observed during real robot experiments with Kilobots. This side project opened up a new dimension to the complexity of the individual and collective behaviors in swarm robotic systems. \nThis talk will take place in person at SCIoI. \nPhoto by Alina Grubnyak on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-mohsen-raoufi/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230615T100000
DTEND;TZID=Europe/Berlin:20230615T110000
DTSTAMP:20260615T142621
CREATED:20230515T103356Z
LAST-MODIFIED:20240813T102222Z
UID:15424-1686823200-1686826800@www.scienceofintelligence.de
SUMMARY:Ulrike Scherer and Sean Ehlman (Science of Intelligence)
DESCRIPTION:Abstract: \nCollective dynamics play a crucial role in everyday decision-making. Whether social influence promotes the spread of accurate information and ultimately results in collective intelligence or leads to false information cascades and maladaptive social contagion depends on the cognitive mechanisms underlying social interactions. \nThis talk will take place in person at SCIoI. \n  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-project-21/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230608T100000
DTEND;TZID=Europe/Berlin:20230608T110000
DTSTAMP:20260615T142621
CREATED:20230320T103137Z
LAST-MODIFIED:20240813T102253Z
UID:15001-1686218400-1686222000@www.scienceofintelligence.de
SUMMARY:Oussama Zenkri and Florian Bolenz (Science of Intelligence)\, "Complex Behavior From Simple Strategies"
DESCRIPTION:Abstract: \nIn our project\, we explore the idea that complex\, intelligent behavior can be generated by selecting from simple strategies in a smart way. In the first part\, we will talk about how we tested this idea of strategy selection in the context of human decision making under risk\, and we will discuss the potential and remaining challenges of this approach. In the second part\, we will move to more complex behavior and present a lockbox-like task that we have designed to investigate strategy learning and strategy selection in human exploration behavior. \nThis talk will take place in person at SCIoI. \n  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-ousama-zenkri-and-florian-bolenz/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230601T100000
DTEND;TZID=Europe/Berlin:20230601T110000
DTSTAMP:20260615T142621
CREATED:20230515T103018Z
LAST-MODIFIED:20250603T125855Z
UID:15421-1685613600-1685617200@www.scienceofintelligence.de
SUMMARY:Milagros Miceli\, “Transparency for Whom? Designing Data Documentation With Data Workers”
DESCRIPTION:Abstract:  \nThe opacity of datasets poses a significant challenge to creating inclusive and intelligible machine learning (ML) systems. Various AI ethics initiatives have addressed this issue by proposing standardized dataset documentation frameworks based on the value of transparency.  In this talk\, I propose a shift of perspective: from documenting for transparency to documenting for reflexivity. Based on a long-term project with outsourced data workers in Argentina\, Bulgaria and Syria\, I argue for the need of designing documentation starting from the needs and experience of the workers who collect\, sort\, and label the data that trains ML models. This requires considering the historical inequalities\, working conditions\, and epistemological standpoints that shape both data work and datasets. \nThis talk will take place in person at SCIoI. \nPhoto by Hunter Harritt on Unsplash \n  \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dr-milagros-miceli/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230511T100000
DTEND;TZID=Europe/Berlin:20230511T110000
DTSTAMP:20260615T142621
CREATED:20230320T101238Z
LAST-MODIFIED:20240813T102328Z
UID:14994-1683799200-1683802800@www.scienceofintelligence.de
SUMMARY:Lauren Sumner-Rooney
DESCRIPTION:More details to follow. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-lauren-sumner-rooney/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230504T100000
DTEND;TZID=Europe/Berlin:20230504T110000
DTSTAMP:20260615T142621
CREATED:20230320T100436Z
LAST-MODIFIED:20250603T125924Z
UID:14992-1683194400-1683198000@www.scienceofintelligence.de
SUMMARY:Radoslaw Cichy\, “Deep Neural Networks As Scientific Models of Vision”
DESCRIPTION:Abstract: \nArtificial deep neural networks (DNNs) are used in many different ways to address scientific questions about how biological vision works. In spite of the wide usage of DNNs in this context\, their scientific value is periodically questioned. I will argue that DNNs are good in three ways for vision science: for prediction\, for explanation\, and for exploration. I will illustrate these claims by recently published or still ongoing projects in the lab. I will also propose future steps to accelerate progress. \nThis talk will take place in person at SCIoI. \nPhoto kindly provided by Radoslaw Cichy. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-radoslaw-cichy/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230420T100000
DTEND;TZID=Europe/Berlin:20230420T110000
DTSTAMP:20260615T142621
CREATED:20230320T095113Z
LAST-MODIFIED:20250603T125937Z
UID:14987-1681984800-1681988400@www.scienceofintelligence.de
SUMMARY:Friedhelm Hamann (Science of Intelligence)\, “Applications of Event Cameras: Animal Behavior Quantification in the Wild”
DESCRIPTION:Abstract: \nEvent cameras are novel bio-inspired sensors that naturally respond to motion in the scene. They have promising advantages\, namely a high dynamic range\, little motion blur and low latency. But how can we leverage these advantages for vision tasks such as animal behavior quantification? In this talk I will  present two applications developed at the Robotic Interactive Perception lab\, where we used event cameras to address practical problems\, from low-level vision (background-oriented schlieren imaging\, a technique for visualizing air flow) to high-level vision (animal behavior quantification in the wild). \nThis talk will take place in person at SCIoI. \nPhoto by Steve Johnson on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scioi-project-36/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230413T100000
DTEND;TZID=Europe/Berlin:20230413T110000
DTSTAMP:20260615T142621
CREATED:20230320T094941Z
LAST-MODIFIED:20250603T125951Z
UID:14984-1681380000-1681383600@www.scienceofintelligence.de
SUMMARY:Nina Poth (Science of Intelligence)\, “Exploring the Prospects for a Prediction-Oriented View of Intelligence”
DESCRIPTION:Abstract: It has recently been proposed that a minimal condition of intelligence is the ability to form accurate predictions (Tjøstheim & Stephens 2021). In this talk\, I evaluate the promise of this view for integrating intelligence research across subdisciplines within the cognitive and life sciences. I argue that this view combines two desirable features: (1) it allows us to subsume key dimensions identifying intelligent behaviour\, such as goal-directedness\, adaptiveness\, generality\, and flexibility (Coelho Mollo 2021; Glock 2019)\, under a unifying conceptual framework; (2) it combines well with a non-symbolic approach to representation at various degrees of abstraction (Gärdenfors 2004). Thereby\, the predictive view provides opportunities for sharing concepts and transforming problems across research on artificial and biological intelligence. However\, an outstanding issue with this approach is its current lack of insight into the relevant mechanisms and functional interactions generating intelligent behavior. I respond to this challenge by discussing a set of available research heuristics for mechanism discovery (Poth 2022).\n\nReferences \nCoelho Mollo\, D. (2022). Intelligent Behaviour. Erkenntnis\, 1-17.\nGärdenfors\, P. (2004). Conceptual spaces as a framework for knowledge representation. Mind and Matter\, 2(2)\, 9-27.\nGlock\, H. J. (2019). Agency\, intelligence and reasons in animals. Philosophy\, 94(4)\, 645-671.\nPoth\, N. (2022). Schema-centred unity and process-centred pluralism of the predictive mind. Minds and Machines\, 32(3)\, 433-459.\nTjøstheim\, T. A.\, & Stephens\, A. (2021). Intelligence as Accurate Prediction. Review of Philosophy and Psychology\, 1-25. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-nina-poth/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230406T100000
DTEND;TZID=Europe/Berlin:20230406T110000
DTSTAMP:20260615T142621
CREATED:20221114T104605Z
LAST-MODIFIED:20240813T102441Z
UID:13325-1680775200-1680778800@www.scienceofintelligence.de
SUMMARY:Xing Li (Science of Intelligence)\, "Learning to Manipulate Articulated Objects From Human Demonstrations"
DESCRIPTION:Abstract: \nProgramming robots to manipulate articulated objects such as drawers\, doors\, or locks is a challenging task. One of the major reasons for this difficulty is that robots must physically interact with objects\, and even minor errors during manipulation can result in significant internal forces that may cause damage. \nWhile robots struggle with these manipulation tasks\, humans can effortlessly operate complex mechanisms with great reliability. Moreover\, humans can transfer their experience between objects of the same type\, resulting in remarkable generalization. This raises the question of how we can transfer these robust and general manipulation skills from humans to robots. \nIn this presentation\, we will introduce a viable solution to achieve this transfer in the context of manipulating articulated objects. Specifically\, we will demonstrate that a robot can acquire a manipulation policy that reliably manipulates various instances of the same type based on a single demonstration of a human opening an articulated object. \nFollowing the presentation\, we invite those who are interested to participate in an interactive session where we can discuss and share our experiences with controlling the robot with the soft hand in the robotics lab on the second floor. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-xing-li/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230330T100000
DTEND;TZID=Europe/Berlin:20230330T110000
DTSTAMP:20260615T142621
CREATED:20230327T091603Z
LAST-MODIFIED:20240813T102500Z
UID:15096-1680170400-1680174000@www.scienceofintelligence.de
SUMMARY:Marah Halawa (Science of Intelligence)\, "Contrastive Learning Approaches for Computer Vision Applications"
DESCRIPTION:Abstract: \nThe recent success in Computer Vision has been mostly attributed to improved results using deep learning models trained on large labeled datasets. Many of these datasets have been labeled by humans. The labeling process\, however\, can be time-consuming\, and in many applications\, it may require expertise that could be costly to acquire. In order to address this requirement\, more research focus and effort have shifted toward unsupervised learning algorithms\, in order to utilize the ever-increasing quantities of unlabeled data. Self-supervised learning (SSL)\, in particular\, is a set of algorithms that specifically aim to learn rich data representations from unlabeled samples\, and it achieves comparable results to fully supervised methods on common benchmarks for image classification and segmentation. The idea behind SSL methods is to learn broad features from the signals that exist in unlabeled data. In other words\, to acquire more general information and knowledge\, and store them as neural network features that will be useful as prior knowledge for subsequent downstream supervised tasks (classification\, segmentation\, regression\, ..etc.). \nThere are two types of SSL methods. First\, self-prediction methods\, which predict some omitted parts (in purpose) of the data using the other existing part of the data\, such as jigsaw puzzle solving. Second\, contrastive learning methods\, which utilize similarities and dissimilarities\, or simply relations\, amongst data samples to form a classification problem\, such as SimCLR (simple contrastive learning of representations). Contrastive learning methods have proven effective as representation learners in applications of natural image classification. Nevertheless\, extending such algorithms to multiple application domains comes with challenges\, and we identify certain limitations in these approaches. Therefore\, in this talk\, we will focus on contrastive learning methods and how to apply them in several computer vision applications. We also discuss the challenges and limitations we identified and how to address them in project 29. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-marah-halawa-contrastive-learning-approaches-for-computer-vision-applications/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230323T100000
DTEND;TZID=Europe/Berlin:20230323T120000
DTSTAMP:20260615T142621
CREATED:20230222T135409Z
LAST-MODIFIED:20240813T102507Z
UID:14755-1679565600-1679572800@www.scienceofintelligence.de
SUMMARY:Dr. Arlena Jung\, "Time Management & Resilience"
DESCRIPTION:Abstract: \nIn this talk\, Dr. Jung will focus on the three key principles of good time management: defining priorities\, managing expectations and developing routines that work. Following the lecture\, the participants have the opportunity to discuss their time management challenges in an individual coaching session. \nDefining Priorities: Dealing with high performance expectations in wide array of areas ranging from research to writing\, presenting\, networking and teaching is a key challenge for early-stage researches. In order to deal effectively with the in part conflicting expectations PhD students and early stage researchers need both the mindset and the self-confidence to define priorities. This means developing short and middle term goals that are both compatible with one’s own long-term goals and the expectations one’s “relevant other’s”. Without clear goals defining priorities and quality criteria become impossible tasks. That participants learn to understand the use of time management tools using the power of the 4 Zs to define SMART goals\, and integrating a “definition of done” into work packages\, milestones and at times even individual tasks. We also address the emotional challenge of dealing with in part conflicting goals\, roles and expectations. Together we discuss how ambiguity tolerance and strategic thinking can be used as key strengths in dealing with the multifaceted challenges but also opportunities of this career phase.  \nManaging Expectations: Complex interdependencies are an inherent part of the qualification phase of early stage research. Without the ability to manage expectations. PhD students have a very limited ability to actually turn their priorities into actionable plans. In this section of the lecture the participants are acquainted with key stakeholder-management tools such as the stakeholder-matrix and the systemic portrait. We\, however\, also discuss key communication skills needed to manage expectations effectively such as “7 shades of no”\, turning “yes” into a deliberate decision and creating solution  oriented dialogues. \nDeveloping routines that work: In order to use the limited resources available as effectively as possible early stage researchers need to learn to develop routines that work. This means figuring out what time management tools fit nicely both with their individual needs and their operational and conceptual tasks. In the last section of the lecture we present time management tools that help PhD students structure their working days and weeks ranging from the pomodoro and the ivy lee method to stimulus-response regulation practices and self-monitoring and self-evaluation methods.\n \n  \nThis talk will take place in person at SCIoI. \nPhoto by freestocks on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dr-arlena-jung-time-management-resilience/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
END:VCALENDAR