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Showing 1 to 11 of 11 for “"Reasoning under uncertainty"”.

  1. Theoretical Principles for Information-Efficient Reasoning under Uncertainty

    Today's machines rely on resource-intensive algorithms and specialized hardware to produce intelligent sensorimotor behavior. In contrast, the brain can transform noisy stimuli into effective actions that solve a wide range of tasks using limited experience, operating with modest processing …

    rice Repository record for Theoretical Principles for Information-Efficient Reasoning under Uncertainty (opens in a new tab)

  2. A methodology for the selection of a paradigm of reasoning under uncertainty in expert system development

    … a methodology for the selection of a paradigm of reasoning under uncertainty for the expert system developer. This is important since practical information on how to select a paradigm of reasoning under uncertainty is not generally available. The thesis explores the role of uncertainty in an …

    edithcowan Repository record for A methodology for the selection of a paradigm of reasoning under uncertainty in expert system development (opens in a new tab)

  3. Argumentation and artifacts for intelligent multi-agent systems

    Reasoning under uncertainty is a human capacity that in software system is necessary and often hidden. Argumentation theory and logic make explicit non-monotonic information in order to enable automatic forms of reasoning under uncertainty. In human organization Distributed Cognition and Activity …

    bologna Repository record for Argumentation and artifacts for intelligent multi-agent systems (opens in a new tab)

  4. Inductive classifier learning from data: An extended Bayesian belief function approach

    A central problem in artificial intelligence is reasoning under uncertainty. This thesis views inductive learning as reasoning under uncertainty and develops an Extended Bayesian Belief Function approach that allows a two-layer representation of the probabilistic rules: basic probabilistic belief …

    uiuc Repository record for Inductive classifier learning from data: An extended Bayesian belief function approach (opens in a new tab)

  5. Schematic Effects on Probability Problem Solving

    … specific conditions and sources of bias in human reasoning under uncertainty. In addition, these biases may be influential when evaluating empirical findings in a manner similar to that demonstrated in this paper experimentally, and may have implications for how social scientists are trained in …

    columbia-diss Repository record for Schematic Effects on Probability Problem Solving (opens in a new tab)

  6. A unified framework for resource-bounded autonomous agents interacting with unknown environments

    … and constructing adaptive autonomous systems under resource constraints. The first part of this thesis contains a concise presentation of the foundations of classical agency: namely the formalizations of decision making and learning. Decision making includes: (a) subjective expected utility …

    cambridge Repository record for A unified framework for resource-bounded autonomous agents interacting with unknown environments (opens in a new tab)

  7. Reasoning under partial observability in heterogeneous networked systems

    … and safely. This thesis addresses the problem of reasoning about correctness, safety, and redundancy in configured networked systems under uncertainty. It argues that this problem can be addressed by introducing a common, easy-to-use semantic layer into which heterogeneous configurations can be …

    uiuc Repository record for Reasoning under partial observability in heterogeneous networked systems (opens in a new tab)

  8. Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases

    Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a …

    unt Repository record for Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases (opens in a new tab)

  9. Approximate Inference: New Visions

    … is the gold standard method to perform coherent reasoning under uncertainty. It is generally believed that intelligent systems following the Bayesian approach can better incorporate uncertainty information for reliable decision making, and be less vulnerable to attacks such as data poisoning. …

    cambridge Repository record for Approximate Inference: New Visions (opens in a new tab)

  10. Autonomy through real-time learning and OpenNARS for Applications

    … reasoner incorporating Non-Axiomatic Reasoning System (NARS) theory is explored. The design and implementation is presented in detail, in addition to the theoretical foundation. Then, experiments related to various system capabilities are carried out and summarized, together with …

    temple Repository record for Autonomy through real-time learning and OpenNARS for Applications (opens in a new tab)

  11. Semantically aware hierarchical Bayesian network model for knowledge discovery in data : an ontology-based framework

    … mining framework that implicitly caters for the underpinning domain knowledge and eventually leads to a more intelligent and accurate mining process. To a certain extent the proposed mining model will simulate the cognitive system in the human being. The similarity between ontology, the Bayesian …

    salford Repository record for Semantically aware hierarchical Bayesian network model for knowledge discovery in data : an ontology-based framework (opens in a new tab)