Course manual 2025/2026

Course content

Formal epistemology uses mathematical and logical tools to explore and answer questions of epistemology and rationality. What makes a system of credences rational? What can/should a rational agent know or believe given a body of evidence? How strongly should they believe? When is a belief justified?  How should a rational agent revise their beliefs and update their knowledge in light of new information? 

This course introduces commonly used technical methods in formal epistemology and treats a collection of selected topics. In particular, we will use probability theory and (modal) logic to formalize notions of (strengths of) belief; and address epistemological issues concerning the nature of rationality, belief revision, logical omniscience, and reasoning about conditionals. Throughout, we will compare qualitative vs. quantitative approaches and assess their relative merits and weaknesses. Topics to be covered include, among others,  Bayesian/probabilistic models of belief and belief revision, rationality constraints on credences, conditional credences and credences of conditionals, arguments for and against Bayesianism, measures for degrees of rationality. (This list is tentative and can be modified due to limited time and to address students' interests.)  

The particular topics and relevant literature will be selected in a way  that the course complements other related courses in the Master of Logic programme, such as Dynamic Epistemic Logic; Topology, Logic and Learning; and Philosophical Logic.

Study materials

Literature

Syllabus

  • can be found on the Canvas page of the course.

Objectives

  • Use logical (qualitative) and probabilistic (quantitative) tools to formalize and address problems in epistemology in novel settings;
  • Compare various formal tools used in formal epistemology and report on their relative merits and weaknesses;
  • Prove mathematical/metalogical results concerning the main concepts introduced in the course;
  • Critically analyze and present (both orally and in writing) research papers on topics covered in the course.

Teaching methods

  • Lecture
  • Seminar
  • Presentation/symposium

Learning activities

Activity

Hours

Hoorcollege

28

Presentatie

6

Werkcollege

14

Self study

120

Total

168

(6 EC x 28 uur)

Attendance

This programme does not have requirements concerning attendance (TER-B).

Assessment

Item and weight Details

Final grade

  • In-class practice (four in total, each counting for 13% of the final grade)
  • Presentations (35%)
  • Opponent Questions (13%)

Details can be found in the course syllabus published on Canvas.

Inspection of assessed work

A date and time for inspection will be announced to the students of the course via Canvas.

Assignments

All assessed and non-assessed components of the course are described in detail in the course syllabus.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Detailed weekly plan of the course can be found on Canvas. 

Week 1: Motivation and Technical Preliminaries

Week 2: Conditional Probabilities, Conditionals, and Triviality

Week 3: Updates and Further Rationality Constraints

Week 4: Further Rationality Constraints - II

Week 5: Arguments for Bayesianism

Week 6: Arguments against Bayesianism

Week 7: Summary of the content and Preperation for Student Presentations

Week 8: Student Presentations

Contact information

Coordinator

  • dr. A. Özgün