Porzel, Robert
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Porzel, Robert
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Porzel, Robert
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Item type:Publication, An Ontological Model of User Preferences(RWTH Aachen, 2023); ; ; ; The notion of preferences plays an important role in many disciplines including service robotics which is concerned with scenarios in which robots interact with humans. These interactions can be favored by robots taking human preferences into account. This raises the issue of how preferences should be represented to support such preference-aware decision making. Several formal accounts for a notion of preferences exist. However, these approaches fall short on defining the nature and structure of the options that a robot has in a given situation. In this work, we thus investigate a formal model of preferences where options are non-atomic entities that are defined by the complex situations they bring about.conference paper18 26 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Narrativizing Knowledge Graphs(RWTH Aachen, 2022); ; ; ; Any natural language expression of a set of facts – that can be represented as a knowledge graph – will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore, propose a specific pipeline that can be applied to produce linguistic narratives from knowledge graphs using an ontological layer and corresponding rules that turn a knowledge graph into a semantic specification for natural language generation. Critically, narratives are seen as necessarily committing to specific perspectives taken on the facts presented. We show how this most commonly neglected facet of producing summaries of facts can be brought under control.conference paper16 32 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards Conflictual Narrative MechanicsWe propose a five steps methodology to retrieve, reconstruct and analyse conflict related narratives in a standardized and automated way. Our methodology combines AI and network analysis techniques to build a visual representation of key agents and entities involved in a conflict and to characterize their relations. Unlike the majority of existing methods, ours can be applied to any type of conflict, as, through two data downloading phases, it first generates a bird’s-eye representation and then a fine-grained map of any conflict. Given the broad applicability of the proposed methodology, we believe that this work moves the first steps towards a better understanding of conflictual narrative mechanics.conference paper25 31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, On Formalizing NarrativesThe activities of people as well as of artificial agents in reality, virtual reality or simulation can be recorded as data that discretize trajectories of body parts and the ensuing force events. While these data provide vast amounts of information they are, by themselves, meaningless. Only when we put them into context we assign a specific meaning to these data. Increasingly, the notion of narratives is being used to describe the result of this semiotic process, i.e. we observe events and fit them into a story that makes sense to us. In this work a formal model is presented and discussed that can be employed to represent a narrative using the subset of FOL that is expressible in OWL DL.conference paper13 38 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Dynamic Action Selection Using Image Schema-based Reasoning for Robots(RWTH Aachen, 2021); ; ; ; Dealing with robotic actions in uncertain environments has been demonstrated to be hard. Many classic planning approaches to robotic action make the closed world assumption, rendering them inefficient for everyday household activities, as they function without generalizability to other contexts or the ability to deal with unexpected changes. In contrast, humans robustly execute underspecified instructions in unfamiliar environments. In this paper, we initiate our research program where we propose the use of functional relations in the form of image-schematic micro-theories, formally represented in ISL𝐹 𝑂𝐿, to enrich action descriptors with semantic components. It builds on the body of work in embodied cognition showing that human conceptualization of action sequences is founded on abstract patterns learned from physical experiences in the form of spatiotemporal relationships between object, agents and environments. These theories are used to inform action selection mechanisms for behavioral robotics written in EL++ and we argue how these micro-patterns can be applied in a more general way to deal with underspecified action commands and commonsense problem-solving.conference paper80 50 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, "My, my, how can i resist you?" - Examining User Reactions to Bogus Explanations of AI PredictionIn human-AI-collaboration tasks, explanations with low faithfulness but high plausibility might be used to invoke unwarranted trust in the AI. We propose the term bogus explanations for these kinds of explanations and compare their effect on participant behavior to that of no explanation, for the task of determining if a Eurovision Song Contest song is a winner or a loser. Our study found that participants tended towards their own intuitive choices. Fewer of the users that were provided with bogus explanations followed the AI’s suggestions and they were more critical of the AI’s performance, but at the same time, they reported that they trusted the AI more than the group without explanations.conference paper32 17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Narrative ObjectsIn this work we operate on the view that the pragmatic employment of objects by an agent is manifested via their affordances for that specific agent. What affordances can manifest themselves in a particular situation depends, in part, on the dispositions offered by the particular objects involved. The contribution of this work is to construct and deploy a large scale formal model of dispositions for physical objects that can be employed to constrain and describe the roles they can play in narratives.conference paper21 20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Conceptual Shadows: Visualizing Concept-specific Dimensions of Meaning in Word Embeddings with Self Organizing MapsWord embeddings (high-dimensional vectors) are common input representations in NLP. However, this kind of representation is not meaningful to humans; it presents a black box that makes it difficult to explain how the vectors influence downstream models. Visualizing word vectors usually requires dimensionality reduction. We explore the visualization of word vectors as 2D images (one image per word, one pixel per vector dimension) by organizing the dimensions in the image with a self-organizing map. This method reveals new insights into how and where semantic information is encoded in the vector and allows us to pinpoint the source of downstream classification errors in the input representation. In this paper, we present the first results of an investigation into word embeddings that visualizes individual word vectors as images and explores what information the individual dimensions of the vectors encode. As this encoded information is specific to the given target concepts of a symbolic downstream classification task, it can be regarded as a projection from the symbolic space to that of the deep neural network.conference paper23 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Panta Rhei: Curiosity-Driven Exploration to Learn the Image-Schematic Affordances of Pouring LiquidsDespite rapid progress, cognitive robots have yet to match the facility with which humans acquire and find ways to reuse manipulation skills. An important component of human cognition seems to be our curiosity-driven exploration of our environments, which results in generalizable theories for action outcome prediction via analogical reasoning. In this paper, we implement a method to emulate this curiosity drive in simulations of the situation of pouring liquids between containers, and to use these simulations to construct a symbolic theory of pouring. The theory links qualitative descriptions of an initial state and manner of pouring with observed behaviors, and can be used to predict qualitative outcomes or select manners of pouring towards achieving a goal.conference paper56 19