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The realization of computational models for accomplishing everyday manipulation tasks for any object and any purpose would be a disruptive breakthrough in the creation of versatile, general-purpose robot agents; and it is a grand challenge for AI and robotics. Humans are able to accomplish tasks such as “cut up the fruit” for many types of fruit by generating a large variety of context-specific manipulation behaviors. They can typically accomplish the tasks on the first attempt despite uncertain physical conditions and novel objects. Acting so effectively requires comprehensive reasoning about the possible consequences of intended behavior before physically interacting with the real world. In the FAME project, I will investigate the research hypothesis that a knowledge representation and reasoning (KR&R) framework based on explictly-represented and machine-interpretable inner-world models can enable robots to contextualize underdetermined manipulation task requests on the first attempt. To this end, I will design, implement, and evaluate FAME (Future-oriented cognitive Action Modelling Engine), a hybrid symbolic/subsymbolic KR&R framework that will contextualize actions by reasoning symbolically in an abstract and generalized manner but also by reasoning with “one’s eyes and hands” through mental simulation and imagistic reasoning. Realizing FAME requires three breakthrough research results: (1) modelling and parameterization of manipulation motion patterns and understanding the resulting effects under uncertain conditions; (2) the ability to mentally simulate imagined and observed manipulation tasks to link them to the robot’s knowledge and experience; and (3) the on-demand acquisition of task-specific causal models for novel manipulation tasks through mental physics-based simulations. To assess the power and feasibility of FAME, I will use open manipulation task learning as a benchmark challenge.
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One of the most pressing scientific challenges today is understanding the fate of our oceans and marine ecosystems under on-going climate change. Unfortunately, anthropogenic stressors act at a rate and magnitude that exceed recent natural variability, making the use of decadal ecological data and time-series insufficient for predictions of future behaviour of marine ecosystems. MICRO2MACRO will reconstruct snapshots of marine pelagic ecosystems between 54 and 32 million years ago (Eocene and early Oligocene), when climate and environmental conditions approximated what we will start to experience in the next century and beyond. Using the microfossil record of planktonic foraminifera (PF), the most complete of any Cenozoic eukaryote, the project will generate the first methodologically controlled (hence reproducible) early Cenozoic global dataset of ecology, abundance, species composition, diversity and biogeography (macroecology) of these prolific pelagic calcifiers. Benefiting from the mole of data generated over the last 15 years, I will learn and apply novel tools in data-science technology to compile ocean temperature and chemistry datasets for the studied time intervals and statistically compare them against the new PF dataset generated with this project. This study will combine the most advanced knowledge in several disciplines (micropaleontology, informatics, statistical ecology) to test for links between time-specific climate (e.g., sea surface temperatures) and ecosystem (e.g., species composition, dominant ecology) configurations, and understand how plankton biogeography was shaped in a warmer world. Hence, MICRO2MACRO will highlight future ecological and evolutionary analogues if the current climate trajectory remains interrupted and we are to hit climate conditions similar to those in the Eocene and Oligocene. Given the uncertainties associated with projections based on modern data this study will represent a major advancement in the field.
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Global law is changing fundamentally. New forms of law creation, new modes of adjudication, and new enforcement mechanisms in the transnational constellation challenge our understanding of law as a state-based phenomenon. The attending boom in research on transnational law has significantly contributed to our understanding of its structure and functioning. However, existing normative accounts of transnational law often still rely on a conception of legal force that originates in the state or a polity. As a result, a distinctive and compelling normative theory of transnational law has yet to be realized. TFL will fill this gap by developing a normative theory of transnational law based on a novel concept of the transnational force of law. This concept has two dimensions: In a descriptive sense, the transnational force of law accounts for the plurality of societal legal forces in the transnational legal arena, beyond public/private and state/non-state dichotomies. In its normative dimension, it requires a sophisticated normative foundation for all of these societal legal forces that takes into account polycentric claims for legitimacy, efficiency, and justice. This is what our normative theory of transnational law will provide. This theory will be operationalized in three case studies on areas of transnational law where new forms of rulemaking coincide with a broad societal discussion on their normative foundation: financial markets (lex financiaria), internet governance (lex digitalis), and agricultural markets (lex agraria). The analysis will proceed in two steps: (1) descriptively, systemizing the respective transnational legal phenomena in terms of legislative, judicial, executive transnational legal forces, and identifying normative conflicts with human, societal and environmental spheres around normative claims for legitimacy, efficiency and justice; (2) normatively, developing ways to realize these demands within these legal arenas.
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