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Modeling Causal Relations

The Workshop "Concrete Causation" on July 9, 2010, at the Seminar for Philosophy, Logic and Philosophy of Science (LMU Munich) will be followed by a seminar (Proseminar) on causal modeling (in English language) in the winter semester 2010/11:

Modeling Causal Relations
(Lecturer: Roland Poellinger)

The topic of this course is the formal treatment of causal relations, about which we obtain information in various ways: Different accounts emphasize mere observation, basal intuition, or intervention in the setting under examination. Starting with Hume’s influence on philosophical research we turn to approaches that emerged in interaction with Statistics and Artificial Intelligence.

View the seminar in the LMU LSF system here.

Topics include:

  1. Counterfactuals and Possible Worlds Semantics
  2. Propensities and Humphreys’ Paradox
  3. Causal Diagrams, Bayesian Networks, Belief Propagation
  4. Causal Decision Theory and Newcombe’s Paradox
  5. Probabilistic Accounts of Causation
  6. Determinism and Invariances
  7. Causal Mechanisms and Modularity
  8. Observation, Intervention, Experiment
  9. Norms, Expectations, Defaults
  10. Ranking Theory


[1] Cartwright, Nancy: Hunting Causes and Using Them: Approaches in Philosophy and Economics. Cambridge University Press, 2007

[2] Cartwright, Nancy: What is Wrong with Bayes Nets? Monist, 2001, 84, 242

[3] Hitchcock, Christopher: Prevention, Preemption, and the Principle of Sufficient Reason. Philosophical Review, 2007, 116, 495-532

[4] Humphreys, Paul: Why Propensities Cannot be Probabilities. Philosophical Review, 1985, 94, 557-570

[5] Lewis, David: Causation. Journal of Philosophy, Journal of Philosophy, 1973, 70, 556-567

[6] Lewis, David: Counterfactuals. Wiley-Blackwell, 1973

[7] Pearl, Judea: Causality: Models, Reasoning, and Inference. Cambridge University Press, 2009

[8] Pearl, Judea: Causal diagrams for empirical research. Biometrika, 1995, 82, 669-688

[9] Spohn, Wolfgang: Bayesian Nets Are All There Is To Causal Dependence. In: Galavotti, M. C. & others (ed.): Stochastic Dependence and Causality, CSLI Publications, Stanford, 2000, 157-172

[10] Spohn, Wolfgang: Causation: An Alternative. The British Journal for the Philosophy of Science, Oxford University Press, 2006, 57, 93-119

[11] Williamson, Jon: Bayesian Nets and Causality: Philosophical and Computational Foundations. Oxford University Press, 2005

[12] Woodward, James: Making Things Happen: A Theory of Causal Explanation (Oxford Studies in the Philosophy of Science). Oxford University Press, 2005


Click here to access the restricted download page.


Please pre-register via e-mail to Roland Poellinger (r.poellinger [at] lmu.de)


Ein Leistungsnachweis kann erzielt werden mit einer Kurzpräsentation und der schriftlichen Ausarbeitung einer philosophischen Problemstellung in Englischer Sprache (Thesis-Defense Paper mit First Draft und Final Draft)


Vorkenntnisse bzgl. klassischer Prädikatenlogik (z.B. im Umfang des "Collegium Logicum") ebenso wie Vorbeschäftigung mit Statistik/Wahrscheinlichkeitstheorie sind hilfreich und wünschenswert, aber nicht erforderlich