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Diese Dissertation beschäftigt sich mit der kooperativen Regelung einer mobilen Arbeitsmaschine, welche aus einem Nutzfahrzeug und einem oder mehreren hydraulischen Manipulatoren besteht. Solche Maschinen werden für Aufgaben in der Straßenunterhaltungsaufgaben eingesetzt. Die Arbeitsumgebung des Manipulators ist unstrukturiert, was die Bestimmung einer Referenztrajektorie erschwert oder unmöglich macht. Deshalb wird in dieser Arbeit ein Ansatz vorgeschlagen, welcher nur das Fahrzeug automatisiert, während der menschliche Bediener ein Teil des Systems bleibt und den Manipulator steuert. Eine solche Teilautomatisierung des Gesamtsystems führt zu einer speziellen Klasse von Mensch-Maschine-Interaktionen, welche in der Literatur noch nicht untersucht wurde: Eine kooperative Regelung zwischen zwei Teilsystemen, bei der die Automatisierung keine Informationen von dem vom Menschen gesteuerten Teilsystem hat. Deswegen wird in dieser Arbeit ein systematischer Ansatz der kooperativen Regelung mit begrenzter Information vorgestellt, der den menschlichen Bediener unterstützen kann, ohne die Referenzen oder die Systemzustände des Manipulators zu messen. Außerdem wird ein systematisches Entwurfskonzept für die kooperative Regelung mit begrenzter Information vorgestellt. Für diese Entwurfsmethode werden zwei neue Unterklassen der sogenannten Potenzialspiele eingeführt, die eine systematische Berechnung der Parameter der entwickelten kooperativen Regelung ohne manuelle Abstimmung ermöglichen. Schließlich wird das entwickelte Konzept der kooperativen Regelung am Beispiel einer großen mobilen Arbeitsmaschine angewandt, um seine Vorteile zu ermitteln und zu bewerten. Nach der Analyse in Simulationen wird die praktische Anwendbarkeit der Methode in drei Experimenten mit menschlichen Probanden an einem Simulator untersucht. Die Ergebnisse zeigen die Überlegenheit des entwickelten kooperativen Regelungskonzepts gegenüber der manuellen Steuerung und der nicht-kooperativen Steuerung hinsichtlich sowohl der objektiven Performanz als auch der subjektiven Bewertung der Probanden. Somit zeigt diese Dissertation, dass die kooperative Regelung mobiler Arbeitsmaschinen mit den entwickelten theoretischen Konzepten sowohl hilfreich als auch praktisch anwendbar ist.

Preregistration of a study where infants can initiate events via their eye-movements that might help them to find relevant information.

The study aims to test how 14-month-old infants interpret actions of information gathering. In conjunction with previous experimental results, it explores whether infants attribute an agent's actions towards obtaining information to achieve their goal more efficiently, or if they see the actions as motivated by mere curiosity.

We aim to investigate whether infants expect others to maximize information gain via their information gathering. We assume that this would require infants to compute information gain that can be expected from the observed agent's perspective. To test this question, we measure infants’ looking time to two actions of an agent in the same situation, both of which can be interpreted as information seeking, have the same cost, but provide different amounts of information. If infants expect others to maximize information gain, they should be surprised and look more at the action that provides less information to the agent.

The aim of this study is to clarify children’s representation of different epistemic states (knowledge, uncertainty, ignorance) by testing their inclination to helpfully communicate to agents who have received different types of evidence.

‎, Zeitschrift für Ostmitteleuropa-Forschung, Bd. 71 Nr. 4 (2022): East Central Europe as a Place of Refuge in the Twentieth Century: State and Patterns of Historical Research

In a series of pioneering studies, Gergely et al. (1995) and Csibra et al. (1999) showed that preverbal infants inferred goals from the observation of efficient actions. Infants were first habituated to animated events in which a ball (A) jumped over an obstacle in order to reach another ball (B), and were later shown two test events featuring the same two balls but no obstacle. Depending on the event, ball A was shown reaching B either by moving in a straight path (Efficient Test event) or by jumping again in an arc motion (Inefficient Test Event). Infants looked longer at the jumping action compared to the straight-path approach, indicating that they found the latter more compatible with the habituation event than the former. In the present study, we seek to replicate these results via an online testing procedure. Given the impact that COVID-19 has had on the ability of infancy researchers to recruit participants for lab-based testing, many scientists are now resorting to online testing. By targeting an established finding in developmental science, which has been repeatedly replicated by a number of labs (e.g., Skerry et al., 2013; Liu & Spelke, 2017), we seek to assess whether online infant-controlled procedures can be suitable methods for running experiments with infants, in spite of the possibly larger noise in data collection that a non-standardized testing environment and equipment might bring.

Although infants can frequently observe others gathering information, it is an open question whether and how they make sense of such activities since both their mental causes and intended effects are hidden and underdetermined by evidence. Still, as information-directed actions provide a unique window into other agents’ epistemic states, particularly their gaps in knowledge, it could be advantageous for social organisms to develop interpretative capacities towards such behaviors, at least for the purposes of competition, exploitation, or cooperation. We test the hypothesis that infants attribute information-seeking goals to agents' actions when these actions could reduce the agents' uncertainty regarding those variables that are relevant for reaching their instrumental goals.

Contrasting possibilities has a fundamental adaptive value for prediction and learning. Developmental research, however, yielded controversial findings. Some data suggest that preschoolers might have trouble in planning actions that take into account mutually exclusive possibilities, while other studies revealed an early understanding of alternative future outcomes based on infants' looking behavior. To better understand the origin of such abilities, we suggest using pupil dilation as a potential indicator of infants' representation of possibilities. In our two previous experiments, ten- and fourteen-month-olds were engaged in an object identification task watching video animations where three different objects with identical top parts moved behind two screens. Importantly, a target object emerged from one of the screens but remained in partial occlusion, revealing only its top part, which was compatible with a varying number of possible identities. We found that pupil diameter increased with the object's potential identities in fourteen- but not in ten-month-olds. In this experiment, we aim to replicate and extend our previous results by showing 14-month-old infants similar object identification tasks as in our previous studies, but here, the identity of the displayed objects will be compatible with not 1 or 2, but with 2 or 3 mutually exclusive possibilities. Just as adults' pupil diameter grows monotonically with the amount of information held in memory, we expect that infants' pupil size will increase with the number of alternatives sustained in memory as candidate identities for the partially-occluded object.

Autonomous driving is a popular research area within the computer vision research community. Since autonomous vehicles are highly safety-critical, ensuring robustness is essential for real-world deployment. While several public multimodal datasets are accessible, they mainly comprise two sensor modalities (camera, LiDAR) which are not well suited for adverse weather. In addition, they lack far-range annotations, making it harder to train neural networks that are the base of a highway assistant function of an autonomous vehicle. Therefore, we introduce a multimodal dataset for robust autonomous driving with long-range perception. The dataset consists of 176 scenes with synchronized and calibrated LiDAR, camera, and radar sensors covering a 360-degree field of view. The collected data was captured in highway, urban, and suburban areas during daytime, night, and rain and is annotated with 3D bounding boxes with consistent identifiers across frames. Furthermore, we trained unimodal and multimodal baseline models for 3D object detection. Data are available at \url{https://github.com/aimotive/aimotive_dataset}., Comment: The paper was accepted to ICLR 2023 Workshop Scene Representations for Autonomous Driving

In spite of ongoing research into infants' early exploratory behavior, the developmental origins of the capacity to adaptively seek out information are still unclear. Particularly, studies with infants rarely quantify and modulate the expected information that subjects can gain by their actions. In a novel eye-tracking paradigm, we investigate 12- to 14-month-olds' ability to adaptively evaluate and select information sources in novel situations. Our paradigm is based on the assumptions that (1) infants can learn statistical contingencies (Saffran & Kirkham, 2018), and (2), similar to human adults (Eliaz & Schotter, 2010) or nonhuman animals (Stagner & Zentall, 2010), infants are driven to gain advance information about future events. We hypothesize that when uncertain about future events, infants are motivated to attend to cues they judge to be more informative regarding these events, using what they have learned about statistical regularities.

The supplementary information contains the Supplementary Notes 1 to 4, with supplementary figures, tables and references

Gaussian blurring is a well-established method for image data augmentation: it may generate a large set of images from a small set of pictures for training and testing purposes for Artificial Intelligence (AI) applications. When we apply AI for non-imagelike biological data, hardly any related method exists. Here we introduce the “Newtonian blurring” in human braingraph (or connectome) augmentation: Started from a dataset of 1053 subjects from the public release of the Human Connectome Project, we first repeat a probabilistic weighted braingraph construction algorithm 10 times for describing the connections of distinct cerebral areas, then for every possible set of 7 of these graphs, delete the lower and upper extremes, and average the remaining 7 − 2 = 5 edge-weights for the data of each subject. This way we augment the 1053 graph-set to 120 $$\times $$ × 1053 = 126,360 graphs. In augmentation techniques, it is an important requirement that no artificial additions should be introduced into the dataset. Gaussian blurring and also this Newtonian blurring satisfy this goal. The resulting dataset of 126,360 graphs, each in 5 resolutions (i.e., 631,800 graphs in total), is freely available at the site https://braingraph.org/cms/download-pit-group-connectomes/. Augmenting with Newtonian blurring may also be applicable in other non-image-related fields, where probabilistic processing and data averaging are implemented.

Although infants can frequently observe others gathering information, it is an open question whether and how they make sense of such activities since the mental causes and intended effects of these are hidden and underdetermined by the available evidence. We tested the hypothesis that infants possess a naive theory that leads them to grasp the purpose of information-gathering actions when they serve as sub-goals of higher-order instrumental goals. We presented 14-month-old infants with actions that were inefficient with respect to the agent’s instrumental goal but could or could not be justified as information-seeking behavior via this theory. We expected longer looks in the condition where the detour could not be justified and the results were in line with our predictions. While this evidence is compatible with our hypothesis, further studies are in progress to rule out alternative interpretations of our findings.

Je devais avoir onze ou douze ans lorsque se produisit ce à quoi je dois d’être devenu musicien. La radio diffusait la Symphonie inachevée de Schubert, et lorsque mes parents me dirent le titre de ce que nous étions en train d’écouter, je découvris avec stupeur que les adultes étaient à même de reconnaître la musique classique. Plus tard, alors que j’étais seul à la maison et que j’écoutais de la musique à la radio, je me rendis compte qu’il s’agissait à nouveau de l’Inachevée. Je demandai à ...

In our previous study we have shown that the female connectomes have significantly better, deep graph-theoretical parameters, related to superior "connectivity", than the connectome of the males. Since the average female brain is smaller than the average male brain, one cannot rule out that the significant advantages are due to the size- and not to the sex-differences in the data. To filter out the possible brain-volume related artifacts, we have chosen 36 small male and 36 large female brains such that all the brains in the female set are larger than all the brains in the male set. For the sets, we have computed the corresponding braingraphs and computed numerous graph-theoretical parameters. We have found that (i) the small male brains lack the better connectivity advantages shown in our previous study for female brains in general; (ii) in numerous parameters, the connectomes computed from the large-brain females, still have the significant, deep connectivity advantages, demonstrated in our previous study., Comment: arXiv admin note: substantial text overlap with arXiv:1501.00727

The human braingraph, or connectome is a description of the connections of the brain: the nodes of the graph correspond to small areas of the gray matter, and two nodes are connected by an edge if a diffusion MRI-based workflow finds fibers between those brain areas. We have constructed 1015-vertex graphs from the diffusion MRI brain images of 395 human subjects and compared the individual graphs with respect to several different areas of the brain. The inter-individual variability of the graphs within different brain regions was discovered and described. We have found that the frontal and the limbic lobes are more conservative, while the edges in the temporal and occipital lobes are more diverse. Interestingly, a "hybrid" conservative and diverse distribution was found in the paracentral lobule and the fusiform gyrus. Smaller cortical areas were also evaluated: precentral gyri were found to be more conservative, and the postcentral and the superior temporal gyri to be very diverse.

Né le 19 février 1926 à Lugos (Roumanie), György Kurtág a étudié à Temesvár avec Magda Kardos (piano) et Max Eisikovits (composition), puis à l'Académie de musique de Budapest avec Pál Kadosa (piano), Leó Weiner (musique de chambre), Sándor Veress et Ferenc Farkas (composition). Contrairement à Ligeti, il est resté en Hongrie, où ses œuvres furent majoritairement créées jusque dans les années quatre-vingt ; il fit un séjour à Paris en 1957-58 (travaillant avec Darius Milhaud et Olivier Messiaen). Il a donné, à partir de 1967, des cours de musique de chambre à l'Académie Franz-Liszt de Budapest, et animé de nombreux stages. Il jouit aujourd'hui d'une réputation internationale. Auteur de grands cycles vocaux sur des textes de Bornemisza, Pilinszky, Dalos, Kafka ou Beckett, il a également composé sept volumes de pièces pianistiques pour les enfants, et toute une série d'œuvres de musique de chambre. Il n'a significativement abordé l'écriture pour orchestre qu'en 1994. Dans ce livre, on trouvera l'ensemble des textes et entretiens de Kurtág lui-même, les témoignages de la chanteuse Adrienne Csengery, de la poétesse Rimma Dalos, et du compositeur György Ligeti, profondément liés à son œuvre et à sa personnalité, ainsi que des études de István Balazs, Peter Szendy, György Kroó et Friedrich Spangemacher sur ses œuvres les plus importantes.

A kiterjesztett ellátási hálózatba már nem csak a megrendelő és beszállítója kapcsolata, hanem a logisztikai folyamatok szempontjából nélkülözhetetlen logisztikai szolgáltatók is bele tartoznak. Tanulmányunk célja, hogy bemutasson néhány alapvető kiterjesztett ellátási hálózati felépítést, és meghatározza azokat a dimenziókat, amelyek ahhoz szükségesek, hogy azonosítani tudjuk a hálózat legkisebb elemzési egységét.