Switch to: Citations

Add references

You must login to add references.
  1. (1 other version)Bayesian Nets and Causality: Philosophical and Computational Foundations.Jon Williamson - 2004 - Oxford, England: Oxford University Press.
    Bayesian nets are widely used in artificial intelligence as a calculus for causal reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover causal relationships. This book, aimed at researchers and graduate students in computer science, mathematics and philosophy, brings together two important research topics: how to automate reasoning in artificial intelligence, and the nature of causality and probability in philosophy.
    Download  
     
    Export citation  
     
    Bookmark   70 citations  
  • (1 other version)Philosophies of probability: Objective bayesianism and its challenges.Jon Williamson - manuscript
    This chapter presents an overview of the major interpretations of probability followed by an outline of the objective Bayesian interpretation and a discussion of the key challenges it faces. I discuss the ramifications of interpretations of probability and objective Bayesianism for the philosophy of mathematics in general.
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  • Motivating objective bayesianism: From empirical constraints to objective probabilities.Jon Williamson - manuscript
    Kyburg goes half-way towards objective Bayesianism. He accepts that frequencies constrain rational belief to an interval but stops short of isolating an optimal degree of belief within this interval. I examine the case for going the whole hog.
    Download  
     
    Export citation  
     
    Bookmark   25 citations  
  • (1 other version)Bayesian nets and causality.Jon Williamson - manuscript
    How should we reason with causal relationships? Much recent work on this question has been devoted to the theses (i) that Bayesian nets provide a calculus for causal reasoning and (ii) that we can learn causal relationships by the automated learning of Bayesian nets from observational data. The aim of this book is to..
    Download  
     
    Export citation  
     
    Bookmark   37 citations  
    • Home | Bibliographies | About PhilArchive | Contact us | Code of conduct

    CDP Phiosophy Documentation Center
    PhilPapers logo by Andrea Andrews and Meghan Driscoll.
    This site uses cookies and Google Analytics (see our terms & conditions for details regarding the privacy implications).

    Use of this site is subject to terms & conditions.
    All rights reserved by The PhilPapers Foundation

    Server: philpapers-web-6b65f85844-kqm7s uwo