Williamson, J.
(2005)
*Objective Bayesian nets.*
In: Artemov, S. and Barringer, H. and Garcez, A.A., eds.
We Will Show Them: Essays in Honour of Dov Gabbay.
College Publications, pp. 713-730.
ISBN 9781904987260.
(The full text of this publication is not available from this repository)

The full text of this publication is not available from this repository. (Contact us about this Publication) |

## Abstract

I present a formalism that combines two methodologies: *objective Bayesianism* and *Bayesian nets*. According to *objective Bayesianism*, an agent's degrees of belief (i) ought to satisfy the axioms of probability, (ii) ought to satisfy constraints imposed by background knowledge, and (iii) should otherwise be as non-committal as possible (i.e. have maximum entropy). *Bayesian nets* offer an efficient way of representing and updating probability functions. An *objective Bayesian net* is a Bayesian net representation of the maximum entropy probability function. I show how objective Bayesian nets can be constructed, updated and combined, and how they can deal with cases in which the agent's background knowledge includes knowledge of qualitative *influence relationships*, e.g. causal influences. I then sketch a number of applications of the resulting formalism, showing how it can shed light on probability logic, causal modelling, logical reasoning, semantic reasoning, argumentation and recursive modelling.

Item Type: | Book section |
---|---|

Subjects: | B Philosophy. Psychology. Religion > B Philosophy (General) Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |

Divisions: | Faculties > Humanities > School of European Culture and Languages |

Depositing User: | Jon Williamson |

Date Deposited: | 10 Nov 2008 20:37 |

Last Modified: | 14 Jan 2010 14:26 |

Resource URI: | http://kar.kent.ac.uk/id/eprint/7369 (The current URI for this page, for reference purposes) |

- Export to:
- RefWorks
- EPrints3 XML
- CSV

- Depositors only (login required):