Cognitive Science Plan

Courses required:

PSYC 6216 Introduction to Cognitive Science (3).
This course presents multiple perspectives on the study of intelligent systems. Broad coverage of such topics as philosophy of mind; human memory processes; reasoning and problem solving; artificial intelligence; language processing (human and machine); neural structures and processes; and vision.   Also included is participation in the cognitive science seminar (Same as ITCS 6216, and ITIS 6216) (Fall Semester).

Courses selected as part of the core:

ITCS 6150. Intelligent Systems. (3)
Prerequisites: full graduate standing or consent of the department. To introduce core ideas in AI. Heuristic versus algorithmic methods; problem solving; game playing and decision making; automatic theorem proving; pattern recognition; adaptive learning; projects to illustrate theoretical concepts. (Fall) (Evenings)

PHIL 6630 – Philosophy of Mind (3).
This course addresses questions concerning the relationship between body and mind, the existence of other minds, the nature of consciousness, and the architecture of cognition.  Approaches to these questions include traditional philosophical sources (emphasizing metaphysics and epistemology) and more recent developments in cognitive science (including the computational model of mind, mental representation, connectionist systems, and artificial intelligence).  Also addressed are ethical and social issues involved in the design and implementation of intelligent systems.  Inquiries bear on issue such as free will and determinism, emotion and reasoning, and the nature of rationality.  (Regularly)

Courses selected from “topics” selection:

ITCS 6156. Machine Learning. (3)
Prerequisite: ITCS 6150 or consent of the department. Machine learning methods and techniques including: acquisition of declarative knowledge; organization of knowledge into new, more effective representations; development of new skills through instruction and practice; and discovery of new facts and theories through observation and experimentation. (On demand)

ITCS 6170. Logic for Artificial Intelligence. (3)
Prerequisite: ITCS 6150 or consent of the department. Introduction to basic concepts of logic for artificial intelligence, including declarative knowledge, inference, resolution, non-monotonic reasoning, induction, reasoning with uncertain beliefs, distributed information systems, intelligent information systems, planning and intelligent-agent architecture. (On demand)

Capstone Course:

PHIL 6920 Thesis.  (3)  Appropriate research and written exposition of that research is required.   (Upon Approval of Department Graduate Committee).

Spare Courses of Interest:

ECGR 5196. Introduction To Robotics. (3)
Prerequisites: ECGR 2103 or MEGR 2101 and senior standing. Modeling of industrial robots including homogeneous transformations, kinematics, velocities, static forces, dynamics, computer animation of dynamic models, motion trajectory planning, and introduction to vision, sensors and actuators (dual-listed with MEGR 4127).

PSYC 6116  Cognition (3).
Concerned with how humans acquire information, retain  information in memory, and use this information to reason and solve problems.  Current emphases include memory, category learning, planning, concept formation,  problem solving, mental models, and knowledge representation. (Alternate Years)

ITCS 6153. Neural Networks. (3)
Prerequisites: ITCS 6114. Topics include: Basic notions and models of artificial neural nets; single layer neural classifiers; multilayer one-way neural nets; single layer feedback networks; neural models of associative memory; self organizing neural nets; translation between neural networks and knowledge bases; applications of neural networks. (Even, Fall) (Evenings)