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Course Criteria
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3.00 Credits
This course will introduce the fundamental questions, findings and methods of cognitive science. The computational approach to cognition and the notion of abstract mental representation are introduced within the interdisciplinary framework of the field. Basic knowledge of cognition, computation, and evolution is surveyed. Symbol systems are described and their role in standard representations is discussed. Artificial neural networks are proposed as a model of both the brain and the mind. Linguistic models are introduced and philosophical challenges are discussed. Fl, Sp-3-
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3.00 Credits
This course is an introduction to neuroanatomy, neurology, evolution, genetics, brain imaging techniques, brain disorders, psychoactive substances, and the phenomenon of consciousness. All topics are contextualized within the study of the mind, assuring both a measure of course coherence and the cognitive science perspective. This course is expressly tailored to the needs of cognitive science students, but it will surely be of interest to students of linguistics, psychology, philosophy, biology and education as well. Prerequisites: Cog 166 or Psy 100 or Lin 100 or instructor permission. Sp-3-
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3.00 Credits
This course centers on computer models of music and the musical mind which are based on theories drawn from the field of Cognitive Science. The course features musically oriented "generative symbol systems" housed in a language called Clay that is accessible on the Web. These systems serve to express assorted musicological theories in computer executable form. Thus, they serve as laboratories in which to conduct a wide variety of investigations within the realm of music cognition. The course also features the modeling of musical objects and processes in CLOS (Common Lisp with Objects). CLOS is a very popular medium for expressing cognitive musicological theories. A wealth of ideas will be explored within the context of CLOS, including the application of genetic algorithm and genetic programming techniques to evolutionary composition and theories of improvisation. Two CLOS packages, CMN (Common Music Notation) and CLM (Common Lisp Music) enable scoring and playing compositions, including experiment driven compositional fragments. Prerequisites: Cog 166 or Mat 125/ Csc 125 or CSC 212. Sp-3-
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3.00 Credits
An examination of the theoretical and practical aspects of robot control and autonomous behavior. Elements of the design, implementation, and analysis of hardware and software agents will be explored. Requisite studies will include the construction of simple circuits, as well as the programming of more elaborate robots and assembly of robot kits. Written analyses of readings taken from various problem domains within robotics, intelligent agency, and other areas of AI will also be required. Prerequisite: CSC 241. Sp-3-
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3.00 Credits
Introduction to the computational study of human and machine intelligence. Discussion of computational models, algorithms, and research in neural processing, vision, memory, learning, reasoning, and information processing. Prerequisite: Csc 241. Ir-3-
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3.00 Credits
This course opens with a short review of work done within the field of Natural Language Processing. It proceeds to establish a foundational framework, grounded in theories of knowledge representation and models of computation, through which the computer modeling of language and linguistic processes can be carefully and methodically examined. Emphasis is placed on symbolic systems, rather than connectionist systems. Network formalism for the representation and processing of language at various levels are discussed. Modern grammars and parsing techniques are presented. Models of discourse developed. Experiments on generative models of the creative use of language are designed and conducted. Prerequisites: Cog 166 and Lin 100. Fl-3-
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3.00 Credits
Study of selected topics in the area of cognitive science providing opportunities for the study of material not covered in current course offerings. Special emphasis will be on emerging areas. This may be repeated for credit with different content. Topics vary from semester to semester. Prerequisites: Cog 166 and at least junior standing. The specific prerequisite(s) will be specified when the course is announced. Ir-1 to 6-
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3.00 Credits
Individual study and research under the direction of cognitive science faculty. Prerequisites: Cog 166 and at least junior standing. Ir-1 to 6-
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3.00 Credits
Explores the application and use of neural networks in a variety of areas in the social and natural sciences. Students will familiarize themselves with a number of different neural network architectures, and will learn to use simulation software to apply neural networks to problems of optimization and forecasting, as well as to explore intellectual issues related to neural networks as an explanatory alternative to the understanding of human behavior. Course grades will be based on participation, successful completion on class exercises, and of applied projects chosen by the student. Prerequisite: upper division standing. Ir-3-
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3.00 Credits
The course will feature interdisciplinary individual research projects of a relatively modest scale. Students will have wide latitude in negotiating a realm of study, as well as the approach to study of the selected topic, so long as the project stands in a justifiable relationship to the computational/representational assumption which unifies the field. Prerequisites: senior status and either (1) a Cognitive Science major with all lower division core requirements of the Cognitive Science degree, and the Writing Across The curriculum and Oral Communication Across the Curriculum requirements met, or (2) a Computer Science major seeking the B.S. degree with a concentration in Artificial Intelligence together with Csc 366. Ir-3-
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