Frederick Eberhardt

Advanced Philosophy of Science

This course is all about scientific laws and scientific entities. Why is it the case that from the evidence that one piece of copper conducts electricity, we feel confident that all pieces of copper conduct electricity, while from the fact that one person in the room is a third son, we don't feel more confident to conclude that all people in the room are third sons? Maybe the generalization in the first case is supported by the fact that copper is a metal and consequently a natural kind, while birth-order is not supported by a natural kind. But then: What is a natural kind such that it supports these lawlike generalizations? And, how do we come to know and identify these building blocks of science? This course is going to cover some of the core literature on these questions. A willingness to engage in formal methods is going to be necessary to succeed.

Great Philosophers

In this course we focus on some of the most important texts in the history of Western philosophy in order to discuss a wide range of central philosophical problems. Among the philosophers most likely to be studied are Plato, Aristotle, Descartes, Hume, Kant, Mill, Marx, Nietzsche, and Wittgenstein. Our goal is not just to appreciate the genius of some great philosophers but also to grapple with the current philosophical problems they have bequeathed to us.

PNP-Seminar: Causal and Probabilistic Reasoning

Causal and Probabilistic Learning Causal knowledge is essential in order to predict how a system will behave when it is subject to an intervention. In many cases we infer causal relations on the basis of probabilistic data. But not every correlation indicates a direct causal relation. So how do we tell the difference? This question has two aspects, one normative, the other descriptive: How ought we infer causal relations from probabilistic data? And on the other hand, how do we actually obtain causal knowledge? This course will address both these questions. We will consider some of the normative theory of causal learning, but also contrast this with studies that analyze causal learning in humans and animals.

Computation and Cognition

This course introduces students to some of the key frameworks for thinking about the mind in computational terms. We will be looking at some basic topics in the theory of computation, in addition to considering philosophical issues raised by computational models of cognitive processes. This course is required for graduate students in the PNP Ph.D. program.

Advanced Philosophy of Science

This course will focus on the role of probability in science. It will include a discussion of the origins of the theory of probability as a tool to improve gambling strategies, the controversy concerning the characterization of randomness in the early 20th century, the development of an axiomatization and the debates between frequentist and subjectivist interpretations of probability. We will consider the implications of such debates for scientific inquiry with a particular emphasis on experimental practice.

Philosophy of Science

This course explores the foundations and justifications of scientific arguments. What is science? To what extent is it objective? How are scientific theories constructed? How are they confirmed? Other topics include induction and probability, the status of theoretical entities, and scientific revolutions.

Problems in Philosophy

This course provides the general introduction to philosophy at Washington University. It covers basic themes in epistemology, ethics and theory of mind. Depending on the instructor, this may also include some philosophy of science.

Causal and Statistical Inference (Summer School)

Assistant to David Danks

This summer session is part of the 2006 Summer School in Logic and Formal Epistemology at Carnegie Mellon. The course introduced students to the methods of causal inference using the causal Bayes net framework.

Nature of Mathematical Reasoning (80-110)

The course is an introduction to mathematical reasoning for non-technical majors. It discusses the axiomatization of geometry and arithmetic as well as the general impact of the incompleteness theorems. It covers some basic propositional and first order logic, including truth tables and simple natural deduction. If time permits, some basic examples of probabilistic reasoning are also presented.

Introduction to Philosophy aka What Philosophy Is, (80-100)

This course provides the general introduction to philosophy at Carnegie Mellon. It covers basic themes in epistemology, ethics and theory of mind. Depending on the instructor, this may also include some philosophy of science.

Nature of Reason (80-150)

The course covers the history of formal methods of reasoning. It presents the basic contrast between inductive and deductive reasoning. It covers Aristotle's syllogisms, medieval proofs of God's existence, Boolean algebra and the development of modern logic, as well as Turing Machines and some examples of probabilistic reasoning. It follows Clark Glymour's book Thinking Things Through.