Order:
Disambiguations
Rolf Haenni [9]R. Haenni [1]R. Haenni [1]
  1.  75
    Probabilistic Logics and Probabilistic Networks.Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler & Jon Williamson - 2011 - Synthese Library.
    Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   17 citations  
  2.  26
    Probabilistic Logic and Probabilistic Networks. Haenni, R., Romeijn, J.-W., Wheeler, G. & Williamson, J. - unknown
    While in principle probabilistic logics might be applied to solve a range of problems, in practice they are rarely applied at present. This is perhaps because they seem disparate, complicated, and computationally intractable. However, we shall argue in this programmatic paper that several approaches to probabilistic logic into a simple unifying framework: logically complex evidence can be used to associate probability intervals or probabilities with sentences.
    Direct download  
     
    Export citation  
     
    Bookmark   23 citations  
  3.  9
    Non-Additive Degrees of Belief.Rolf Haenni - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of Belief. Springer. pp. 121--159.
    Direct download  
     
    Export citation  
     
    Bookmark   3 citations  
  4. Modeling Partially Reliable Information Sources: A General Approach Based on Dempster-Shafer Theory.Stephan Hartmann & Rolf Haenni - 2006 - Information Fusion 7:361-379.
    Combining testimonial reports from independent and partially reliable information sources is an important epistemological problem of uncertain reasoning. Within the framework of Dempster–Shafer theory, we propose a general model of partially reliable sources, which includes several previously known results as special cases. The paper reproduces these results on the basis of a comprehensive model taxonomy. This gives a number of new insights and thereby contributes to a better understanding of this important application of reasoning with uncertain and incomplete information.
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  5.  8
    Probabilistic Argumentation.Rolf Haenni - 2009 - Journal of Applied Logic 7 (2):155-176.
  6.  19
    Combining Probability and Logic.Fabio Cozman, Rolf Haenni, Jan-Willem Romeijn, Federica Russo, Gregory Wheeler & Jon Williamson - 2009 - Journal of Applied Logic 7 (2):131-135.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  7.  27
    Special Issue of Minds and Machines on Causality, Uncertainty and Ignorance.Stephan Hartmann & Rolf Haenni (eds.) - 2006 - Springer.
    In everyday life, as well as in science, we have to deal with and act on the basis of partial (i.e. incomplete, uncertain, or even inconsistent) information. This observation is the source of a broad research activity from which a number of competing approaches have arisen. There is some disagreement concerning the way in which partial or full ignorance is and should be handled. The most successful approaches include both quantitative aspects (by means of probability theory) and qualitative aspect (by (...)
    Direct download (6 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  8.  31
    Causality, Uncertainty and Ignorance.Rolf Haenni & Stephan Hartmann - 2006 - Minds and Machines 16 (3).
    Special issue. With contributions by Malcolm Forster, Rocio Garcia-Rotamero and Ulrich Hoffrage, Christian Jakob, Kevin Korb and Erik Nyberg, Michael Smithson, Daniel Steel, Brad Weslake, and Jon Williamson.
    Direct download  
     
    Export citation  
     
    Bookmark  
  9. Model-Based Diagnostics and Probabilistic Assumption-Based Reasoning.J. Kohlas, B. Anrig, R. Haenni & P. A. Monney - 1998 - Artificial Intelligence 104 (1-2):71-106.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  10.  98
    Possible Semantics for a Common Framework of Probabilistic Logics.Gregory Wheeler, Jon Williamson, Jan-Willem Romeijn & Rolf Haenni - 2008 - In V. N. Huynh (ed.), International Workshop on Interval Probabilistic Uncertainty and Non-Classical Logics. Springer.
    Summary. This paper proposes a common framework for various probabilistic logics. It consists of a set of uncertain premises with probabilities attached to them. This raises the question of the strength of a conclusion, but without imposing a particular semantics, no general solution is possible. The paper discusses several possible semantics by looking at it from the perspective of probabilistic argumentation.
    Direct download  
     
    Export citation  
     
    Bookmark  
  11. Logical Relations in a Statistical Problem.Jon Williamson, Jan-Willem Romeijn, Rolf Haenni & Gregory Wheeler - 2008 - In Benedikt Lowe, Jan-Willem Romeijn & Eric Pacuit (eds.), Foundations of the Formal Sciences Vi: Probabilistic Reasoning and Reasoning With Probabilities. Studies in Logic. College Publications.
    This paper presents the progicnet programme. It proposes a general framework for probabilistic logic that can guide inference based on both logical and probabilistic input. After an introduction to the framework as such, it is illustrated by means of a toy example from psychometrics. It is shown that the framework can accommodate a number of approaches to probabilistic reasoning: Bayesian statistical inference, evidential probability, probabilistic argumentation, and objective Bayesianism. The framework thus provides insight into the relations between these approaches, it (...)
     
    Export citation  
     
    Bookmark