Courses One Page Flyer Spring 2011
SySc 527/627: Discrete System Simulation
The mathematical basis for discrete system simulation (DSS) is probability theory and queuing theory. It is used extensively in the fields of operations research, civil engineering, industrial engineering, systems analysis, etc. Students learn how to use DSS to model systems of interest.
SySc 557/657: Artificial Life
"Artificial Life" (ALife) is a name given to theoretical, mathematical, and computationally "empirical" studies of phenomena commonly associated with "life," such as replication, metabolism, morphogenesis, learning, adaptation, and evolution. It focuses on the materiality-independent, i.e., abstract, bases of such phenomena. As such, it overlaps extensively with "theoretical biology" and, less extensively, with certain areas of physics and chemistry and the social sciences. It also raises important philosophical questions. It is part of a larger research program into "complex adaptive systems," one stream of contemporary systems theory.
In its intersection with computer science, ALife is the newest example of "the sciences of the artificial" (Herbert Simon). ALife is to life what AI is to intelligence. Christopher Langton writes that "Artificial Life ... complements the traditional biological sciences ... by attempting to synthesize life-like behaviors within computers and other artificial media." The purpose is twofold: to understand these phenomena better and to develop new computational technologies.
The course will sample the research literature in this field, and will be organized in a seminar format. Topics to be emphasized are: (1) discrete dynamics: cellular automata and random networks, (2) ecological & evolutionary dynamics, (3) genetic algorithm optimization and adaptation, (4) agent-based simulation. Other topics will include: artificial and real chemistry (metabolism, reproduction, & origin of life), "complex adaptive systems," autonomous agents, and philosophical issues.
Information on Artificial Life research
For more information, see the Spring 2008 Syllabus
SySc 576: AI: Neural Networks II
MW 4:00-5:50, Room TBA
George Lendaris, 725-4988 firstname.lastname@example.org
Focuses on applications. Topics in fuzzy set theory, control theory, and pattern recognition are studied and incorporated in considering neural networks. A Design project (using NN simulator) in selected application area is done by each student.
More Information: Neural Networks II, Spring 2011