Formal epistemology

Formal epistemology is a subdiscipline of epistemology that uses formal methods from logic, probability theory and computability theory to elucidate traditional epistemic problems.

Topics

Some of the topics that come under the heading of formal epistemology include:

• Ampliative inference (including inductive logic);
• Game theory and decision theory;
• Algorithmic learning theory (computational epistemology);
• Formal theories of coherence;
• Foundations of probability and statistics;
• Formal approaches to my bumparadoxes of belief and/or action.

History

Though formally oriented epistemologists have been laboring since the emergence of formal logic (if not earlier), only recently have they been organized under a common disciplinary title. This gain in popularity may be attributed to the organization of yearly Formal Epistemology Workshops by Branden Fitelson and Sahotra Sarkar, starting in 2004, and the recent PHILOG-conferences starting in 2002 (The Network for Philosophical Logic and Its Applications) organized by Vincent F. Hendricks.

Contemporary Formal Epistemologists

• Horacio Arló-Costa, Department of Philosophy, Carnegie Mellon University (Bayesian epistemology, epistemic logic, belief revision, conditionals, rational choice, normative and behavioral decision theory)
• Luc Bovens (Bayesian epistemology, probability, etc)
• Samir Chopra (belief revision, physics, etc)
• Jake Chandler (Bayesian epistemology, belief revision, etc.)
• John Collins (knowledge, causation, vagueness, etc.)
• Franz Dietrich (collective decision-making, etc.)
• Igor Douven (Bayesian epistemology, etc.)
• Ellery Eells (confirmation, probability)
• Adam Elga (probabilistic reasoning, laws, etc)
• Branden Fitelson (confirmation, logic, etc)
• Malcolm Forster (confirmation, simplicity, causation)
• Anthony Gillies (belief revision, formal semantics)
• Mario Gómez-Torrente
• Alan Hájek (foundations of probability, decision theory, etc.)
• Joseph Halpern (reasoning about knowledge and uncertainty)
• Sven Ove Hansson (risk, decision theory, belief revision, deontic logic)
• Gilbert Harman (epistemology, statistical learning theory, mind and language)
• Stephan Hartmann (Bayesian epistemology, probability, collective decision-making, etc.)
• James Hawthorne (confirmation theory, inductive logic, belief revision, nonmonotonic logic)
• Vincent F. Hendricks (epistemic logic, formal epistemology)
• Franz Huber (formal epistemology, philosophy of science, philosophical logic)
• Richard Jeffrey (probabilistic reasoning)
• James Joyce (decision theory)
• Kevin T. Kelly, Department of Philosophy, Carnegie Mellon University (computational epistemology, belief revision, etc)
• Matthew Kotzen (formal epistemology, philosophy of science)
• Marion Ledwig (Newcomb's problem)
• Hannes Leitgeb (belief revision, probability, Bayesianism, etc.)
• Isaac Levi (belief revision)
• Patrick Maher (confirmation, inductive logic)
• David Miller (probability, induction, logic, Popper)
• Luca Moretti (confirmation, coherence, transmission of warrant, epistemic truth)
• Daniel Osherson (inductive logic, reasoning, vagueness)
• Gabriella Pigozzi (belief revision, decision theory)
• John Pollock (decision theory, reasoning, AI)
• Darrell Rowbottom (foundations of probability, confirmation, philosophy of science, etc.)
• Teddy Seidenfeld Department of Philosophy, Carnegie Mellon University (statistical decision theory, probability theory, game theory)
• Wolfgang Spohn (reasoning, probability, causation, philosophy of science, etc)
• Paul Thorn (direct inference, defeasible reasoning, induction, etc)
• Peter Vranas (confirmation, deontic logic, time travel, ethics, etc)
• Gregory Wheeler (statistical reasoning, default logic, probabilistic logic)
• Roger White (confirmation, cosmology)
• Jon Williamson (Bayesianism, probability, causation)
• Timothy Williamson (knowledge, modality, logic, vagueness, etc)
• David Wolpert (No Free Lunch theorems, i.e., Hume done rigorously; physics and inference, i.e., monotheism theorems, Chomsky hierarchy of inference devices, etc.)

References

• Bovens, L. and Hartmann, S. (2003). Bayesian Epistemology. Oxford: Oxford University Press.
• Hendricks, V. F. (2001). The Convergence of Scientific Knowledge: A View from The Limit. Dordrect: Kluwer Academic Publishers.
• Hendricks, V. F. (2006). Mainstream and Formal Epistemology. New York: Cambridge University Press.
• Hendricks, V. F. (ed.) (2006). Special issue on “8 Bridges Between Mainstream and Formal Epistemology”, Philosophical Studies.
• Hendricks, V. F. (ed.) (2006). Special issue on “Ways of Worlds I-II”, Studia Logica.
• Hendricks, V.F. and Pritchard, D. (eds.) (2006). New Waves in Epistemology. Aldershot: Ashgate.
• Hendricks, V. F. and Symons, J. (eds.) (2005). Formal Philosophy. New York: Automatic Press / VIP. [1]
• Hendricks, V. F. and Symons, J. (eds.) (2006). Masses of Formal Philosophy. New York: Automatic Press / VIP. [2]
• Hendricks, V. F. and Hansen, P.G. (eds.) (2007). Game Theory: 5 Questions. New York: Automatic Press / VIP. [3]
• Hendricks, V.F. and Symons, J. (2006). Epistemic Logic. The Stanford Encyclopedia of Philosophy, Stanford. CA: USA.
• Wolpert, D.H., (1996) The lack of a priori distinctions between learning algorithms, Neural Computation, pp. 1341-1390.
• Wolpert, D.H., (1996) The existence of a priori distinctions between learning algorithms, Neural Computation, pp. 1391-1420.
• Wolpert, D.H., (2001) Computational capabilities of physical systems. Physical Review E, 65(016128).
• Zhu, H.Y. and R. Rohwer, (1996) No free lunch for cross-validation, pp. 1421- 1426.

External links

• Formal Epistemology Workshop
• Formal Epistemology Archive
• Carnegie Mellon Summer School in Logic and Formal Epistemology
• Formal Philosophy
• Formal Epistemology, a free online journal.
• The Reasoner
• Formal Epistemology Project

See also

• Algorithmic learning theory
• Bayesian inference
• Belief revision
• Computability theory
• Computational learning theory
• Decision theory
• Epistemology
• Game theory
• Inductive logic
• Machine learning
• Probability theory
• Statistics