Sample Curriculum:

Cognition, AI, and Philosophy of Mind

The Ph.D. program is also jointly run with the university's renowned program in Computer Science. The Philosophy department is also literally next door to one of the preeminent departments of cognitive psychology in the nation and has close ties with the University's Center for Automated Learning and Discovery and the Language Technology Institute. Nobel Laureate and University Professor Herb Simon is a member of the department, jointly with the departments of Psychology and Computer Science. Other faculty with research interests in this area include Horacio Arlo-Costa, Clark Glymour, Kevin Kelly, Mandy Simons, and Teddy Seidenfeld. Several of the faculty have significant research interests in machine learning, knowledge representation, belief revision, automated discovery, and the history and philosophy of cognitive science. .

This convergence of resources provides one of the best opportunities in the nation to apply results and concepts from artificial intelligence and cognitive science to issues in the philosophy of mind.

Sample Curriculum

This sample curriculum is offered to illustrate how the core requirements of the program can be met by a student interested in Cognitition, AI, and Philosophy of Mind. Students are welcome to design programs more closely attuned to their own interests.

Fall First Year

• Research Seminar: Introduces students to research topics in the department.
• Minds, Machines and Knowledge: Implications of the computational model of mind for epistemology, and vice-versa
• Logic and Computability: Syntax and semantics of first-order logic.
• Elective: e.g., Cognitive Processes and Problem Solving: A survey of the "Human Problem Solving" paradigm in cognitive psychology (taught by Prof. Herb Simon, jointly appointed in Psychology, Computer Science, and Philosophy).

Spring First Year

• Probability and Artificial Intelligence: Anintroduction to contemporary probabilistic methods in AI, including neural nets and Bayes nets.
• Computability and Incompleteness: Godel's theorems, computability, and their epistemological significance.
• Elective: e.g., Probability and Mathematical Statistics I: Research tools for empirical psychology
• Elective: e.g., Introduction to Parallel Distributed Processing: Overview of network models, including perception, memory, language, knowledge representation and learning.

Fall Second Year

• Elective: e.g., Philosophy of Mind:Contemporary topics in philosophy of mind, especially issues in the logic of belief.
• Elective e.g., philosophy seminar: e.g., Seminar on Metaphysics: Contemporary metaphysical views and their connections with philosophical logic.
• Elective: e.g., Machine Learning: This course covers the theory and practice of machine learning from a variety of perspectives.
• Elective: e.g., Probability and Mathematical Statistics I: Research tools for empirical psychology

Spring Second Year

• Research symposium: Students present their master's thesis projects.
• Elective: e.g., Seminar on Epistemology: Contemporary issues in the theory of knowledge, including new issues in the logic of knowledge representation and learnability.
• Elective: e.g., Seminar on the Philosophy of Science: Contemporary issues in the logic of confirmation, explanation, realism, causation, and in particular sciences.
• Elective: e.g., Computer Vision: How to make robots that see.

Fall Third Year

• Directed Reading
• Dissertation Research
• Elective: e.g., Seminar in Higher Level Cognition and Brain Function: Implications of recent brain imaging studies.
• Elective: e.g., Recursion and hierarchies:Uncomputability with applications to learning

Spring Third Year

• Directed Reading
• Dissertation Research
• Elective: e.g., Computational Models of Neural Systems: In-depth study of information processing in real neural systems from a computer science perspective
• Elective: e.g., Biology of the Brain: Electrophysiology of neurons; human neuroanatomy, anatomy and functioning of the sensory system, and molecular genetics of the nervous system.