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New Courses in CS Date: Friday, March 13, 1998.
- COM S 201 "Cognitive Science in Context Laboratory: Explorations of Cognitive Science in Ecological Settings"
- COM S 202 "Transition to Java"
- COM S 522 "Computational Tools and Methods for Finance"
- COM S 619 "Principles of Distributed Computing -- Shared Memory"
- COM S 626 "Computational Molecular Biology"
- COM S 674 "Natural Language Understanding"
- COM S 686 "Logics of Programs"
COM S 201 "Cognitive Science in Context Laboratory: Explorations of Cognitive
Science in Ecological Settings"
To be taught this coming fall by Professor Halpern.
An intensive laboratory course that explores the theories of
cognitive science, and provides direct experience with the techniques of cognitive
science, in relation to the full range of both present and anticipated-future activities
in the workplace, the classroom, and in everyday life. Discussion of laboratory exercise
results, supplementation of laboratory topics, and analysis of challenging primary
research literature are done in meetings of the entire class, while smaller groups meet to
carry out laboratory exercises that include student-developed experiments. Use of the
Internet and Web sites are integral components of the course. State of the art computing,
display (visual, auditory, and other perceptual/sensory systems), digital communication,
and simulation approaches, are used to apply cognitive science principles and concepts to
the analysis, exploration, and direct testing of human-machine interfaces and
human-computer interactions that are intended to permit effective and efficient exchange
of information and control of functions or operations. This approach is applied to real
life settings such as interactions with touch screen displays, computer-based natural
language processing, Internet and World Wide Web communications involving individual and
group video displays, use of 'neural networks', and personal and group transportation
vehicles and systems. Students are expected to come to each discussion meeting having read
and thought about assigned materials, and to come to scheduled laboratory meetings fully
prepared to perform the laboratory exercises. Laboratory facilities will be available to
students at all times so that statistical analysis of data, preparation of laboratory
reports, and collection of experimental data, will be facilitated.
Problems and algorithms in computational molecular biology. Topics include
sequences (alignment, scoring functions, complexity of searches and alignment, secondary
structure prediction, families and function), the protein folding problem (lattice models,
lattice searches, the HP model, chemical potentials, statistical potentials, funnels,
complexity and model verification, global optimization, homology, threading), and the
dynamics of complex biosystems (the Molecular Dynamics method, long range forces,
statistics of flexible systems, reduced models).
This course presents an introduction to natural language processing, the
primary concern of which is the study of human language use from a computational
perspective. The course will cover syntactic analysis, semantic interpretation, and
discourse processing, via symbolic and statistical approaches. Possible topics include
information extraction, natural language generation, memory models, ambiguity resolution,
finite-state methods, mildly context-sensitive formalisms, deductive approaches to
interpretation, machine translation, and machine learning of natural language.
Topics in logics of programs and program verification. Possible topics include: Floyd/Hoare logic, modal logic, dynamic logic, temporal logic, process logic, automata on infinite objects and their relation to program logics, the Rabin tree theorem, the modal mu-calculus, games and alternating automata, applications to type inference, set constraints, Kleene algebra.
Last updated January 04, 1999. For more information email us at ugrad@cs.cornell.edu .