2,805 research outputs found

    1. Helgoland Power and Energy Conference - 24. Dresdener Kreis 2023

    Get PDF
    Der Sammelband "1. Helgoland Power and Energy Conference" beinhaltet neben einem kurzen Bericht zum 24. Treffen des Dresdener Kreises 2023 wissenschaftliche Beiträge von Doktoranden der beteiligten Hochschulinstitute zum Thema Elektroenergieversorgung. Der Dresdener Kreis setzt sich aus der Professur für Elektroenergieversorgung der Technischen Universität Dresden, dem Fachgebiet Elektrische Anlagen und Netze der Universität Duisburg-Essen, dem Fachgebiet Elektrische Energieversorgung der Leibniz Universität Hannover und dem Lehrstuhl Elektrische Netze und Erneuerbare Energie der Otto-von-Guericke Universität Magdeburg zusammen und trifft sich einmal im Jahr zum fachlichen Austausch an einer der beteiligten Universitäten

    Multidisciplinary perspectives on Artificial Intelligence and the law

    Get PDF
    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Spatial adaptive settlement systems in archaeology. Modelling long-term settlement formation from spatial micro interactions

    Get PDF
    Despite research history spanning more than a century, settlement patterns still hold a promise to contribute to the theories of large-scale processes in human history. Mostly they have been presented as passive imprints of past human activities and spatial interactions they shape have not been studied as the driving force of historical processes. While archaeological knowledge has been used to construct geographical theories of evolution of settlement there still exist gaps in this knowledge. Currently no theoretical framework has been adopted to explore them as spatial systems emerging from micro-choices of small population units. The goal of this thesis is to propose a conceptual model of adaptive settlement systems based on complex adaptive systems framework. The model frames settlement system formation processes as an adaptive system containing spatial features, information flows, decision making population units (agents) and forming cross scale feedback loops between location choices of individuals and space modified by their aggregated choices. The goal of the model is to find new ways of interpretation of archaeological locational data as well as closer theoretical integration of micro-level choices and meso-level settlement structures. The thesis is divided into five chapters, the first chapter is dedicated to conceptualisation of the general model based on existing literature and shows that settlement systems are inherently complex adaptive systems and therefore require tools of complexity science for causal explanations. The following chapters explore both empirical and theoretical simulated settlement patterns based dedicated to studying selected information flows and feedbacks in the context of the whole system. Second and third chapters explore the case study of the Stone Age settlement in Estonia comparing residential location choice principles of different periods. In chapter 2 the relation between environmental conditions and residential choice is explored statistically. The results confirm that the relation is significant but varies between different archaeological phenomena. In the third chapter hunter-fisher-gatherer and early agrarian Corded Ware settlement systems were compared spatially using inductive models. The results indicated a large difference in their perception of landscape regarding suitability for habitation. It led to conclusions that early agrarian land use significantly extended land use potential and provided a competitive spatial benefit. In addition to spatial differences, model performance was compared and the difference was discussed in the context of proposed adaptive settlement system model. Last two chapters present theoretical agent-based simulation experiments intended to study effects discussed in relation to environmental model performance and environmental determinism in general. In the fourth chapter the central place foragingmodel was embedded in the proposed model and resource depletion, as an environmental modification mechanism, was explored. The study excluded the possibility that mobility itself would lead to modelling effects discussed in the previous chapter. The purpose of the last chapter is the disentanglement of the complex relations between social versus human-environment interactions. The study exposed non-linear spatial effects expected population density can have on the system and the general robustness of environmental inductive models in archaeology to randomness and social effect. The model indicates that social interactions between individuals lead to formation of a group agency which is determined by the environment even if individual cognitions consider the environment insignificant. It also indicates that spatial configuration of the environment has a certain influence towards population clustering therefore providing a potential pathway to population aggregation. Those empirical and theoretical results showed the new insights provided by the complex adaptive systems framework. Some of the results, including the explanation of empirical results, required the conceptual model to provide a framework of interpretation

    The development of an international model for technology adoption: the case of Hong Kong

    Get PDF
    The purpose of this study is to examine the causal relationships between the internal beliefs formation of a decision-maker on technology adoption and the extent of the development of a technology adoptive behaviour. In particular, this study aims to develop an International Model For Technology Adoption (IMTA), which builds upon the Theory of Planned Behaviour (Ajzen 1992) and improves on the framework of the Technology Acceptance Model (Davis 1986). The development of such a model requires an understanding of the environmental factors which shape the cognitive processes of the decision maker. Hence, this is a behavioural model which investigates the constructs influencing the adoption behaviour and how the interaction between these constructs and the external variables can impact on the decision making process at the level of the firm. Previous research on technology transfer and innovation diffusion has classified factors affecting the diffusion process into two dimensions: 1) external-influence and 2) internal-influence. Hence, in this research, the International Model For Technology Adoption looks at how the endogenous and exogenous factors enter into the cognitive process of a technology adoption decision through which attitudes and behavioural intentions are shaped. Under the IMTA, the behavioural intention to adopt is a function of two exogenous variables, 1) Strategic Choice, and 2) Environmental Control. The Environmental Control factor is further categorised by two exogenous factors, namely, 1) Government Influence, and 2) Competitive Influence. In addition, the Competitive Influence factor is, in turn, classified into five forces: namely, 1) Industry Structure, 2) Price Intensity, 3) Demand Uncertainty, 4) Information Exposure, 5) Domestic Availability. Regarding the cognitive process which forms the attitude to adopt, it is hypothesised to be affected by six other endogenous beliefs: 1) Compatibility; 2) Enhanced Value; 3) Perceived Benefits; 4)Adaptative Experiences, 5) Perceived Difficulty; and 6) Suppliers’ Commitment. A survey research method was utilised in this study and the research instrument was developed after a comprehensive review of the relevant literature and an expert interview. A total of 298 completed questionnaires were returned; giving a response rate of 13.56%. Of the 298 questionnaires, 39 of the responses were unusable with missing date. This gives a total of 259 usable questionnaires and an effective response rate of 11.78%. The results of the analysis suggested that the fitness of the International Model For Technology Adoption was good and the data of this study supported the overall structure of the IMTA. When compared with the null model, which was used by the EQS as a baseline model to judge to overall fitness for the IMTA, the IMTA yielded a value of 0.914 in the Comparative Fit index; hence, indication of a good fit model. In addition, the results of the principal component analysis also illustrated that the 16-factor International Model For Technology Adoption was an adequate model to capture the information collected during the survey. The results shown that this 16-factor structure represented nearly 77% of the total variance of all items. A further analysis into the factor structure, again, revealed that there existed a perfect match between the conceptual dimensionality of the International Model For Technology Adoption and the empirical data collected in the survey. However, the results of the hypotheses testing on the individual constructs were mixed. While not all the magnitude of these ten hypotheses was statistically significant, almost all pointed to the direction conceptualised by the IMTA. From these results, it can be interpreted that while the results of the structural equation modelling analysis provided overall support to the International Model For Technology Adoption, the results of individual constructs of the Model revealed that some constructs were forming a larger impact than others in the decision making process to adopt foreign technology. In particular, the intention to adopt was greatly affected by the attitude of the prospective adopters, the influence of the government and the degree of industry rivalry. However, the impact of the overall competitive influence factor on the intention to adopt was not supported by the results. Again, the existence of investment alternative was also not a serious concern for the prospective adopters

    Latent Emission-Augmented Perspective-Taking (LEAPT) for Human-Robot Interaction

    Full text link
    Perspective-taking is the ability to perceive or understand a situation or concept from another individual's point of view, and is crucial in daily human interactions. Enabling robots to perform perspective-taking remains an unsolved problem; existing approaches that use deterministic or handcrafted methods are unable to accurately account for uncertainty in partially-observable settings. This work proposes to address this limitation via a deep world model that enables a robot to perform both perception and conceptual perspective taking, i.e., the robot is able to infer what a human sees and believes. The key innovation is a decomposed multi-modal latent state space model able to generate and augment fictitious observations/emissions. Optimizing the ELBO that arises from this probabilistic graphical model enables the learning of uncertainty in latent space, which facilitates uncertainty estimation from high-dimensional observations. We tasked our model to predict human observations and beliefs on three partially-observable HRI tasks. Experiments show that our method significantly outperforms existing baselines and is able to infer visual observations available to other agent and their internal beliefs

    Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks

    Full text link
    Despite the basic premise that next-generation wireless networks (e.g., 6G) will be artificial intelligence (AI)-native, to date, most existing efforts remain either qualitative or incremental extensions to existing ``AI for wireless'' paradigms. Indeed, creating AI-native wireless networks faces significant technical challenges due to the limitations of data-driven, training-intensive AI. These limitations include the black-box nature of the AI models, their curve-fitting nature, which can limit their ability to reason and adapt, their reliance on large amounts of training data, and the energy inefficiency of large neural networks. In response to these limitations, this article presents a comprehensive, forward-looking vision that addresses these shortcomings by introducing a novel framework for building AI-native wireless networks; grounded in the emerging field of causal reasoning. Causal reasoning, founded on causal discovery, causal representation learning, and causal inference, can help build explainable, reasoning-aware, and sustainable wireless networks. Towards fulfilling this vision, we first highlight several wireless networking challenges that can be addressed by causal discovery and representation, including ultra-reliable beamforming for terahertz (THz) systems, near-accurate physical twin modeling for digital twins, training data augmentation, and semantic communication. We showcase how incorporating causal discovery can assist in achieving dynamic adaptability, resilience, and cognition in addressing these challenges. Furthermore, we outline potential frameworks that leverage causal inference to achieve the overarching objectives of future-generation networks, including intent management, dynamic adaptability, human-level cognition, reasoning, and the critical element of time sensitivity

    Learning logic specifications for soft policy guidance in POMCP

    Get PDF
    Partially Observable Monte Carlo Planning (POMCP) is an effi- cient solver for Partially Observable Markov Decision Processes (POMDPs). It allows scaling to large state spaces by computing an approximation of the optimal policy locally and online, using a Monte Carlo Tree Search based strategy. However, POMCP suffers from sparse reward function, namely, rewards achieved only when the final goal is reached, particularly in environments with large state spaces and long horizons. Recently, logic specifications have been integrated into POMCP to guide exploration and to satisfy safety requirements. However, such policy-related rules require manual definition by domain experts, especially in real-world sce- narios. In this paper, we use inductive logic programming to learn logic specifications from traces of POMCP executions, i.e., sets of belief-action pairs generated by the planner. Specifically, we learn rules expressed in the paradigm of answer set programming. We then integrate them inside POMCP to provide soft policy bias toward promising actions. In the context of two benchmark sce- narios, rocksample and battery, we show that the integration of learned rules from small task instances can improve performance with fewer Monte Carlo simulations and in larger task instances. We make our modified version of POMCP publicly available at https://github.com/GiuMaz/pomcp_clingo.git

    The Transformation and Transformational Potential of Religion: Modernity, Secularism, and Humanist Chaplaincy

    Get PDF
    The practice of clinical pastoral care, otherwise termed spiritual care or chaplaincy, in North American and European hospitals provides a case study to explore the historic and ongoing tension between religious worldviews and its others. The tension between religion and modernity, scientific rationalism, secularity, and humanism, among others, have all been presented in dichotomous and hierarchical either/or terms to justify a social imaginary that sees religion in decline. I will argue, firstly, that the very construction of ‘religion and …’ signifies a particular understanding of religion’s nature and role in the episteme of contemporary western societies; and secondly, that in this context, what we mean by religion is currently in flux, that is, ‘religion’ is currently undergoing a significant transformation. Ultimately, I will argue that the transformational potential of religion is not merely its ability to evolve along epistemic shifts but its ability to redescribe the relations between disparate domains. It is within this discursive space that a focus on clinical pastoral care/chaplaincy in modern healthcare contexts provides a particularly appropriate lens through which to reveal the fissures, transformations, and potential for redescription of religion in the 21st century and to begin to imagine its role in mapping the ecological networks between disparate domains. In modern healthcare settings, the role of clinical pastoral care is positioned at a nexus between the patient body, religious or spiritual needs, and a set of totalising secular, materialist, and scientistic discourses. A superficial consideration which assumes these narratives to be incompatible will be challenged by a more nuanced analysis showing the mutual imbrication and necessary tension between such worldviews. In this sense my proposed thesis is part of a broader phenomenological analysis of the current constructions of the nature and role of religion in secular society

    Risk-aware shielding of Partially Observable Monte Carlo Planning policies

    Get PDF
    Partially Observable Monte Carlo Planning (POMCP) is a powerful online algorithm that can generate approximate policies for large Partially Observable Markov Decision Processes. The online nature of this method supports scalability by avoiding complete policy representation. However, the lack of an explicit policy representation hinders interpretability and a proper evaluation of the risks an agent may incur. In this work, we propose a methodology based on Maximum Satisfiability Modulo Theory (MAX-SMT) for analyzing POMCP policies by inspecting their traces, namely, sequences of belief- action pairs generated by the algorithm. The proposed method explores local properties of the policy to build a compact and informative summary of the policy behaviour. Moreover, we introduce a rich and formal language that a domain expert can use to describe the expected behaviour of a policy. In more detail, we present a formulation that directly computes the risk involved in taking actions by considering the high- level elements specified by the expert. The final formula can identify risky decisions taken by POMCP that violate the expert indications. We show that this identification process can be used offline (to improve the policy’s explainability and identify anomalous behaviours) or online (to shield the risky decisions of the POMCP algorithm). We present an extended evaluation of our approach on four domains: the well-known tiger and rocksample benchmarks, a problem of velocity regulation in mobile robots, and a problem of battery management in mobile robots. We test the methodology against a state-of- the-art anomaly detection algorithm to show that our approach can be used to identify anomalous behaviours in faulty POMCP. We also show, comparing the performance of shielded and unshielded POMCP, that the shielding mechanism can improve the system’s performance. We provide an open-source implementation of the proposed methodologies at https://github.com/GiuMaz/XPOMCP

    University of Windsor Graduate Calendar 2023 Spring

    Get PDF
    https://scholar.uwindsor.ca/universitywindsorgraduatecalendars/1027/thumbnail.jp
    corecore