Bayesian Epistemology: Perspectives and Challenges

Conference at Ludwig-Maximilians University of Munich. Deadline: January 11, 2020

The conference on 12-14 August 2020 is preceded by a Summer School on 10-11 August 2020.

Idea & Motivation

Bayesian epistemology remains the dominant account of rational beliefs, it underpins the dominant account of decision making in science and beyond, as well as many of our statistical methods.

While important applications continue to to emerge, the work on the foundations of Bayesian epistemology never stops and a number of challenges are emerging.

The aim of this conference is bring together scholars exploring applications, challenges and foundations of Bayesian epistemology.

Topics of interest (in alphabetic order) are not limited to:

  • Accuracy
  • Bayesianism and Artificial Intelligence
  • Bayesian Networks
  • Bounded Rationality
  • Causation
  • Confirmation
  • Disagreement
  • Evidence
  • Evidence Aggregation
  • Expansion
  • Foundational Aspects of Bayesian Statistics
  • Higher Order Evidence
  • Imprecise Bayesian Approaches
  • Induction
  • Inference
  • Interpretations of Probabilities
  • Judgement Aggregation
  • Maximum Entropy (Applications, Inference and Methods)
  • Multi Agent Epistemology
  • Objective Bayesian Epistemology
  • Principles of Bayesianism (Conditionalisation, Probabilism, Total Evidence)
  • Replication
  • Updating Procedures (Jeffrey, KL, L&P).

Speakers for the Conference

  • James Joyce (Michigan)
  • Gerhard Schurz (Düsseldorf)

Speakers for the Summer School

  • James Joyce (Michigan)
  • Gerhard Schurz (Düsseldorf)
  • Naftali Weinberger (MCMP, LMU Munich)
  • Jürgen Landes (MCMP, LMU Munich)


Reduced fee (for graduate students): 50 EUR
Regular fee: 80 EUR
Members of the MCMP and LMU: participation free of charge

The conference dinner is not included.

Registration information will follow in due time.


  • Jürgen Landes (MCMP, LMU Munich)


Main University Building
Geschwister-Scholl-Platz 1
80539 München

Further Information (LINK)