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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231102T100000
DTEND;TZID=Europe/Berlin:20231102T110000
DTSTAMP:20260615T131035
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:20260615T131035
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:20260615T131035
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
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/09/markus-spiske-70Rir5vB96U-unspla.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231005T100000
DTEND;TZID=Europe/Berlin:20231005T110000
DTSTAMP:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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:20260615T131035
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
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230309T100000
DTEND;TZID=Europe/Berlin:20230309T110000
DTSTAMP:20260615T131035
CREATED:20230207T103252Z
LAST-MODIFIED:20240813T102512Z
UID:14155-1678356000-1678359600@www.scienceofintelligence.de
SUMMARY:Judith L. Bronstein (University of Arizona)\, "Why Cooperate with Another Species? The Puzzles of Mutualism"
DESCRIPTION:Abstract:\nThe classic view of nature is one of a deathly struggle for existence. Yet\, throughout nature\, organisms cooperate with each other. Mutualisms – mutually beneficial interactions between species – are more than fascinating natural history stories: they are central to the diversity and the diversification of life on Earth. Charles Darwin\, well aware of mutualisms\, mused that if species could be shown to act exclusively for the good of others\, “it would annihilate my theory”. The very young field of mutualism research attempts in part to address Darwin’s challenge. I will first briefly discuss the relationship between within-species cooperation and mutualism. I will then introduce two underlying concepts that are helping to guide our growing understanding: mutualism not only confers benefits but also exacts costs on the participants; and the immediate interests of mutualists commonly conflict. Then\, I will review some of my group’s recent findings that help address two of the most vexing puzzles mutualism poses: if mutualisms are beneficial\, why isn’t the world covered with them; and if mutualisms are costly\, then why doesn’t everyone cheat their partners? Our understanding of mutualism has exploded in recent years\, but this new focus has come at the cost of exploring connections between and mutualism and other forms of interaction – a situation I am working to mend during my Wiko fellowship. I will conclude by highlighting the interfaces that excite me the most.\n\nThis talk will take place in person at SCIoI. \n  \nPhoto by Joseph Sharp on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-judith-l-bronstein-university-of-arizona-why-cooperate-with-another-species-the-puzzles-of-mutualism/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230223T100000
DTEND;TZID=Europe/Berlin:20230223T110000
DTSTAMP:20260615T131035
CREATED:20221114T105022Z
LAST-MODIFIED:20240813T101537Z
UID:13332-1677146400-1677150000@www.scienceofintelligence.de
SUMMARY:Ryan Burnell\, "A Cognitive Approach to the Evaluation of AI Systems"
DESCRIPTION:Abstract: \nThe capabilities of AI systems are improving rapidly\, and these systems are being deployed in increasingly complex and high-stakes contexts\, from self-driving cars to the detection of medical conditions. As the importance of AI grows\, so too does the need for robust evaluation. If we want to determine the extent to which systems are safe\, effective\, and unbiased\, it is vital that we understand the cognitive capabilities of those systems. In this endeavour\, psychological science has a lot to offer—scientists from cognitive\, developmental\, and comparative psychology have spent many decades developing theories and paradigms to understand the cognitive capabilities of adults\, children\, and animals. Drawing on these theories and paradigms\, we are working to build a framework for evaluating the cognitive capabilities of AI systems that we hope can be used to better track and regulate AI progress. I will present an initial version of the framework and discuss the open questions and challenges of applying cognitive science to AI evaluation. \nThis talk will take place in person at SCIoI. \nPhoto by Michael Dziedzic on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-ryan-burnell-a-cognitive-approach-to-the-evaluation-of-ai-systems/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230216T100000
DTEND;TZID=Europe/Berlin:20230216T110000
DTSTAMP:20260615T131035
CREATED:20230207T104351Z
LAST-MODIFIED:20240813T101551Z
UID:14161-1676541600-1676545200@www.scienceofintelligence.de
SUMMARY:Julten Abdelhalim (Science of Intelligence)\, "Tips and Guidelines for your grant application in Germany"
DESCRIPTION:Abstract: \nThis talk will be targeting junior postdocs and phd at their final stages. It will be a short and brief introduction to the major options for grants (those aiming at the stars or smaller ones). Julten will offer some quick tips on the application process. She will also share her own experience in applying to the DFG Sachbeihilfe and ERC Starting Grant. The talk is not a detailed workshop in which we get into details about the proposal writing but rather a summary and a call out for how you should ideally plan your grant application journey. Those interested in detailed consultation are invited to book appointments later.\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-julten-abdelhalim-our-career-as-a-scientist-make-a-plan-for-successful-grant-applications/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T160000
DTEND;TZID=Europe/Berlin:20230209T173000
DTSTAMP:20260615T131035
CREATED:20230119T092829Z
LAST-MODIFIED:20240813T101605Z
UID:14065-1675958400-1675963800@www.scienceofintelligence.de
SUMMARY:Oliver Brock (Science of Intelligence)\, "About the Interplay of Embodiment and Learning in Intelligent Systems"
DESCRIPTION:Abstract:\nBiological intelligent systems manifest their intelligence in physical interactions with other agents and with their environment. Such interactions require embodiment. Intelligence\, both artificial and biological\, also requires some kind of learning. But what is the relationship between the two? How should the two interact? Do they even have to? What could be a common ground on which this relationship can be explored\, negotiated\, and ultimately designed? In this presentation\, I will attempt to provide my personal answers to these questions. I will argue that one of the reasons (deep) machine learning has not yet been able to replicate its smashing successes in the context of robotics lies in the widespread disregard for the important capabilities provided by the body. Instead of considering embodiment\, machine learning seems to be resorting to massive use of physical simulations. This seems to be unnecessarily complicated without being convincingly effective.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-oliver-brock-2/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T100000
DTEND;TZID=Europe/Berlin:20230209T110000
DTSTAMP:20260615T131035
CREATED:20230116T111824Z
LAST-MODIFIED:20250603T130020Z
UID:14047-1675936800-1675940400@www.scienceofintelligence.de
SUMMARY:Andreagiovanni Reina (Université Libre De Bruxelles)\, “The Power of Inhibition for Collective Decision Making in Minimalistic Robot Swarms”
DESCRIPTION:Abstract:\nI investigate how large groups of simple robots can reach a consensus with decentralized minimalistic algorithms. Simple robots can be useful in nanorobotics and in scenarios with low-cost requirements. I show that through decentralized voting algorithms\, swarms of minimalistic robots can make best-of-n decisions. In my research\, I show that using a biologically-inspired voting model based on inhibitory signals\, the swarm can collectively perform better and be more resilient against a minority of misbehaving robots than in models without inhibition. Our best-of-n decision algorithm can also be used for collective environmental monitoring. I will show that investigating these models can be very interesting and yield surprising results. As Anderson said in 1972\, More is different. In our analysis\, we found that limiting the communication range or the speed of the robots can improve collective performance in a range of relevant conditions. We explain the mechanisms of some of these phenomena with a combination of mathematical models and large-scale robot experiments.\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-giovanni-rena/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230126T100000
DTEND;TZID=Europe/Berlin:20230126T110000
DTSTAMP:20260615T131035
CREATED:20221128T133841Z
LAST-MODIFIED:20240813T101630Z
UID:13403-1674727200-1674730800@www.scienceofintelligence.de
SUMMARY:Scott Robins (Bonn University)\, "What Machines Shouldn't Do"
DESCRIPTION:Abstract: \nFrom writing essays to evaluating potential hires\, machines are doing a lot these days. In all spheres of life\, it seems that machines are being delegated more and more decisions. Some of these machines are being delegated decisions that could have significant impact on human lives.Examples of such machines which have caused such impact are widespread and include machines evaluating loan applications\, machines evaluating criminals for sentencing\, autonomous weapon systems\, driverless cars\, digital assistants\, etc. Considering that machines cannot be held morally accountable for their actions (Bryson\, 2010; Johnson\, 2006; van Wynsberghe & Robbins\, 2018)\, the question that governments\, NGOs\, academics\, and the general public should be asking themselves is: how do we keep meaningful human control (MHC) over these machines? \n\nThe literature thus far details what features the machine or the context must have in order for MHC to be realized. Should humans be in the loop or on the loop? Should we force machines to be explainable? Lastly\, should we endow machines with moral reasoning capabilities? (Ekelhof\, 2019; Floridi et al.\, 2018; Robbins\, 2019a\, 2019b; Santoni de Sio & van den Hoven\, 2018; Wendall Wallach & Allen\, 2010; Wendell Wallach\, 2007). Rather than look to the machine itself or what part humans have to play in the context\, I argue here that we should shine the spotlight on the decisions that machines are being delegated. Meaningful human control\, then\, will be about controlling what decisions get made by machines. \n\nI argue that keeping meaningful human control over machines (especially AI which relies on opaque methods) means restricting machines to decisions that do not require a justifying explanation and can\, in principle\, be proven efficacious. Because contemporary methodologies in AI are opaque\, many machines cannot offer explanations for their outputs. In many cases\, decisions require justifying explanations\, and we should therefore not use machines for such cases. It won’t be surprising that machines should be efficacious if they are to be used – especially in contexts that will have impacts on human beings. Increasingly\, however\, machines are being delegated decisions for which we are unable\, in principle\, to evaluate their efficacy. This should not happen. \n\nThese arguments lead to the conclusion that machines should be restricted to descriptive outputs. It must always be a human being deciding how to employ evaluative terms as these terms not only refer to specific states of affairs but also say something about how the world ought to be. Machines which are able to make decisions based on opaque considerations should not be telling humans how the world ought to be. This is a breakdown of human control in the most severe way. Not only would we be losing control over specific decisions in specific contexts\, but we would be losing control over what descriptive content grounds evaluative classifications. \n\nIn this talk\, I will first discuss what it means to say that a machine is ‘doing’ something. I then briefly discuss different proposals for MHC and why they fall short. I then argue that machines should not be delegated evaluative decisions as they require justifying explanations which machines cannot give and cannot be evaluated for efficacy. While this talk is framed negatively\, it is my hope that this focuses research and development to design and build machines to help us realize our visions for how the world ought to be\, rather than machines that tell us hour the world ought to be. Only humans can decide that.\n \nThis talk will take place in person at SCIoI. \nPhoto by David Levêque on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scott-robins-bonn-university-what-machines-shouldnt-do/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230119T100000
DTEND;TZID=Europe/Berlin:20230119T113000
DTSTAMP:20260615T131035
CREATED:20230116T101152Z
LAST-MODIFIED:20250603T130050Z
UID:14043-1674122400-1674127800@www.scienceofintelligence.de
SUMMARY:David Garzón Ramos (Université Libre De Bruxelles)\, “Automatic Design of Robot Swarms: Context and Experiments”
DESCRIPTION:Abstract:\n \nSwarm robotics is a promising approach to the coordination of large groups of robots. Traditionally\, the design of collective behaviors for robot swarms has been an iterative manual process: a human designer manually refines the control software of the individual robots until the desired collective behavior emerges.\n\nIn this talk\, I discuss automatic design as an alternative approach to manual design. In automatic methods\, the design process is cast into an optimization problem: given a task to be performed by the swarm\, an optimization process designs a collective behavior to perform the task and produces appropriate control software for the robots. I focus on experiments that highlight the various aspects of the automatic design of robot swarms: classes of collective behaviors\, control architectures\, and the optimization process. In particular\, I present a case study on the design of shepherding behaviors for groups of robots. The results presented in this talk are outcomes of the project DEMIURGE; an ERC funded project devoted to the study of the automatic design of robot swarms (PI Mauro Birattari).\nThis talk will take place in person at SCIoI. \nPhoto by Omar Flores on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-david-garzon-ramos-universite-libre-de-bruxelles-automatic-design-of-robot-swarms-context-and-experiments/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230112T100000
DTEND;TZID=Europe/Berlin:20230112T110000
DTSTAMP:20260615T131035
CREATED:20221128T133344Z
LAST-MODIFIED:20250603T130102Z
UID:13400-1673517600-1673521200@www.scienceofintelligence.de
SUMMARY:Dustin Lehmann\, Fritz Francisco\, Jorg Raisch\, Pawel Romanczuk (Science of Intelligence)\, “Dynamical Adaptation and Learning: Knowledge Transfer and Cooperative Learning in Groups of Heterogeneous Agents”
DESCRIPTION:Abstract: \nIn groups of agents learning how to solve a common task\, interaction and knowledge transfer between agents is important and can vary depending on network topology. Heterogeneity is one of the key principles that influences the type and quality of interaction between learning agents. Different learning strategies and behaviors can be a driving factor for the learning success at the group and individual level\, whereas differences in dynamics (or capabilities\, behaviors\, internal states\, etc.) can impede the direct transferability of knowledge and may require dynamic adaption of the agents.\nIn this talk\, we show how to infer behavioral heterogeneity in learning groups of fish and how this affects future learning capabilities. Prior knowledge of social partners affects the outcome of learning processes and timing of information uptake. We further investigate behavioral heterogeneity from the perspective of synthetic dynamic systems and how to transfer knowledge between dissimilar agents to enable cooperative learning of how to solve a common task. First results show how to exploit heterogeneity for learning in synthetic agents and which information gradient is beneficial when dealing with novel tasks in a social context.\n \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dustin-lehmann-fritz-francisco-jorg-raisch-pawel-romanczuk-dynamical-adaptation-and-learning-knowledge-transfer-and-cooperative-learning-in-groups-of-heterogeneous-agents/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221215T100000
DTEND;TZID=Europe/Berlin:20221215T110000
DTSTAMP:20260615T131035
CREATED:20220914T121043Z
LAST-MODIFIED:20250603T130137Z
UID:13049-1671098400-1671102000@www.scienceofintelligence.de
SUMMARY:Robert Lange and Luis Gomez (Science of Intelligence)\, “Quantifying and Modelling Collective Behavior Across Ecological Contexts”
DESCRIPTION:Abstract: \nA central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret such collective concept\, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as study system. We have combined analytical behavioral characterizations of schools of these fish with synthetic state-of-the-art machine learning methods to understand the  functionality of the behavior in real life. In this talk\, we will show our main findings related to the collective behavior. We will show i) that the highly synchronized diving behavior of the school is close to criticality\, ii) how this can be functionally related to effective communication about predator attacks\, and iii) how to study the heterogeneity in collectives by inferring the parameters of models using machine learning algorithms. \nThis talk will take place in person at SCIoI.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p12/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221208T100000
DTEND;TZID=Europe/Berlin:20221208T110000
DTSTAMP:20260615T131035
CREATED:20221128T100636Z
LAST-MODIFIED:20250603T130147Z
UID:13385-1670493600-1670497200@www.scienceofintelligence.de
SUMMARY:Erik Rodner “Please Label Me: Challenges and Efficient Strategies for Data Annotation and Selection”
DESCRIPTION:Abstract: \nLack of data and annotations has been the showstopper for machine learning projects when I started my PhD and 15 years later it still is. In my talk\, I will give a brief overview of recent models we developed for weakly- and semi supervised as well as for active learning.\nIn addition\, we will analyze the relevance of these algorithms from an industrial perspective\, which often contradicts with the usual story line in traditional computer vision publications. \nThis talk will take place in person at SCIoI. \n  \nPhoto by vackground.com on Unsplash
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-erik-rodner-please-label-me-challenges-and-efficient-strategies-for-data-annotation-and-selection/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221201T100000
DTEND;TZID=Europe/Berlin:20221201T110000
DTSTAMP:20260615T131035
CREATED:20220914T121438Z
LAST-MODIFIED:20240813T101934Z
UID:13054-1669888800-1669892400@www.scienceofintelligence.de
SUMMARY:David Bierbach (Science of Intelligence)\, "Anticipation in social interactions among live and artificial agents"
DESCRIPTION:Abstract: \nThe aim of SCIoI’s P10 is to investigate how anticipation and prediction shapes social interactions among live and artificial agents using for example the Robofish system. We will outline our research showing the sophisticated anticipation abilities of live fish\, as well as how we integrated prediction and anticipation into Robofish’s social interaction behaviors. We will furthermore show how experiments with robotic animals can help to promote animal welfare and what is necessary to build biomimetic robots that will be accepted by live animals as conspecifics (see also these articles: https://www.frontiersin.org/articles/10.3389/fbioe.2020.00441/full\,  https://www.annualreviews.org/doi/10.1146/annurev-control-061920-103228\, https://link.springer.com/chapter/10.1007/978-3-030-64313-3_26 ). Finally we will dive into our public outreach activities that include the Robofish exhibition in the Humboldt Labor at Stadtschloss Berlin with more than 100\,000 visitors since 2021. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p10-jens-krause-verena-hafner-2/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T113000
DTEND;TZID=Europe/Berlin:20221124T130000
DTSTAMP:20260615T131035
CREATED:20221117T101332Z
LAST-MODIFIED:20240813T101103Z
UID:13344-1669289400-1669294800@www.scienceofintelligence.de
SUMMARY:Thursday morning talk: Nicolas Mandel\, "Kangaroos & Quadcopters"
DESCRIPTION:Abstract: \nThe contents of this presentation will be twofold. In the first part the Centre for Robotics of the Queensland University of Technology (QUT) and its research directions and facilities will be introduced. The research on semantics for the benefit of UAVs\, specifically quadcopters\, will be highlighted. The second part will contain the personal experiences of the presenter of undertaking a PhD in Australia\, highlighting differences\, challenges and lessons learnt along the way.Disclaimer: The views and opinions in this talk are the presenters and do not necessarily reflect the opinions of any of the employers or affiliates.\nThis talk will take place in person at SCIoI. \n  \nPhoto by Indy Bruhin on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-nicolas-mandel-kangaroos-quadcopters/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
END:VCALENDAR