Overview of Network & Complex Systems Courses at IUB

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• Overview of Network Complex Systems Courses at
  IUB
• IUB Faculty
• Network Complex Systems Talk, August 29, 2005

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Overview

• P582 Biological and Artificial Neural Networks by
  John Beggs, Physics
• Artificial Life as Approach to AI by Larry
  Yaeger, Informatics
• INFO-I 400/590 Biologically Inspired Computing by
  Luis Rocha, Informatics
• The Simplicity of Complexity by Alessandro
  Vespignani Alessandro Flammini, Informatics
• TEL603 Communication Networks by J. Alison
  Bryant, Telecommunications
• 400/590 Structure of Information Environments by
  Peter Todd, Psychology Informatics
• CS B538 Computer Networks by Minaxi Gupta,
  Computer Science
• L597 Structural Data Mining Modeling by Katy
  Börner, SLIS
• L600 Networks Complex Systems talks Katy
  Börner, SLIS

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Biological and Artificial Neural Networks by
John Beggs, Physics

• P 582 Biological and Artificial Neural Networks,
  3 credits
• Format Three weekly classes, regular homework,
  and a final project presentation.
• Meetings Mon, Wed, Fri 125p-215p in Swain
  West 218
• Text Neural Networks, an introduction, by
  Muller, Reinhardt, and Strickland
• We will first cover the biological details of
  neurons that are thought to be computationally
  relevant. Next we will explore major artificial
  neural network theories and models, many of which
  draw from statistical physics. Finally, we will
  cover experimental data from living neural
  networks and critically evaluate neural network
  theories that claim to describe biological
  phenomena.

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Artificial Life as approach to AI by Larry
Yaeger, Informatics

• Informatics I400/I590 Topics course
  (grad/undergrad), 3 credits
• Format Weekly lecture and discussion. One class
  project, one presentation, three or four exams
  (can drop one).
• This course covers
• Bottom-up design informed by top-down analysis
• Definitions and quantifications of life and
  intelligence
• Genetic algorithms
• Neural networks
• The evolution of learning
• Intelligence as an emergent property
• Computational ecologies / artificial worlds
• Information theory and complexity measures
• Students do weekly readings, provide a
  presentation on one reading, prepare a
• project, and participate in class online
  discussion. All reading materials are
• online, except the required text Valentino
  Braitenbergs Vehicles Experiments
• in Synthetic Psychology
• Class Webpage http//informatics.indiana.edu/larr
  yy/I400.htm

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INFO-I 400/590 Biologically Inspired Computing by
Luis Rocha, Informatics

• What is Life?
• What is Computation?
• Imitation of Life
• Artificial Life and Complex Systems
• Evolutionary Algorithms
• Learning
• Collective Behavior
• Computer Immune Systems
• Bio-inspired Artifacts
• Bio-inspired algorithms in Computational Biology
• Computing with Natural Means

Web page http//informatics.indiana.edu/rocha/i-bi
c Blog http//life-inspired.blogspot.com/
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Communication Networks by J. Alison Bryant,
Telecommunications

• TEL graduate course, 3 credits
• Format Lecture/discussion with 2-3 in-class labs
  throughout the semester. 2-3 assignments and a
  course paper.
• This seminar is intended to
• focus on network formulations of selected
  communication, organizational, social-psychologica
  l, and sociological theories
• review theoretical, conceptual, and analytic
  issues associated with network perspectives on
  communication
• emphasize the influences and consequences of
  communication patterns, processes, and content
• Text Monge, P.R., Contractor, N.S. (2003).
  Theories of Communication Networks. New York
  Oxford.
• This course will be taught Fall 2005 as TEL 603.

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Structure of Information Environments by Peter
Todd, Informatics/Cog.Sci.

• Informatics I400/I590 Topics course
  (grad/undergrad), cross-listed in Cognitive
  Science Tu-Th 1-215 pm, Business 209 3 credits
  
• Format Discussion of papers presentations led
  by students.
• This course covers
• How information is structured in environments
  that people encounter cues, distributions,
  sequential patterns, etc.
• Ways of describing information patterns
• How decision mechanisms take advantage of
  information structure
• How people create information structure
  intentionally and unintentionally
• Structure in social, cultural, and institutional
  environments
• How to create information structure to aid human
  decision making
• Course structure Students read papers for each
  class and come up with discussion questions for
  each one, present one or two papers during the
  term and lead the discussion around everyones
  questions, and critically evaluate one paper in
  writing. Papers will be distributed in class.
• Class webpage in OnCourse CL

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The Simplicity of Complexity by Alessandro
Vespignani Alessandro Flammini, Informatics

• INFO 400/590 Topics in Informatics, 3 credits
• Format Two weekly classes and two bring-home
• assignments and a final project presentation.
• Time Mon, Wed 100p-215p in SY 241
• 16 Students 10 undergrads (all Info)
• 6 grads ( 1I1CS4PHY)
• ..The course is meant to provide a set of
  interpretative tools, both theoretical and
  computational, that will help to better describe,
  model and understand Complexityas we perceive it
  today, the final aim being able to see the
  "unifying picture" beyond the foggy curtain of
  peculiaritities that individual complex system
  may display..

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FRACTALS
CHAOS
STRANGE ATTRACTORS
COMPLEX SYSTEMS
COMPUTATION RECURSIVITY
ORDER FROM DISORDER
MODELING SIMULATION
SCALE INVARIANCE
COMPLEX ARCHITECTURE
EMERGENT BEHAVIOR
NETWORKS
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Communication Networks by J. Alison Bryant,
Telecommunications

• TEL graduate course, 3 credits
• Format Lecture/discussion with 2-3 in-class labs
  throughout the semester. 2-3 assignments and a
  course paper.
• This seminar is intended to
• review theoretical, conceptual, and analytic
  issues associated with network perspectives on
  social interaction and communication
• focus on network formulations of selected
  communication, organizational, social-psychologica
  l, and sociological theories
• approach social science from multi-level,
  multi-theoretical network perspective
• discuss how to use network theory as a starting
  point for network research
• Text
• Monge, P.R., Contractor, N.S. (2003). Theories
  of Communication Networks. New York Oxford.
• Tuesdays, 930am-1200pm
• RTV 169
• This course begins tomorrow.

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CSCI B538 Computer Networks Minaxi Gupta,
Computer Science Dept

• CS graduate course (3 credits)
• Time/Venue Tue/Thur 800-915am, LH 102
• Prerequisites a undergraduate networking/OS
  course, programming experience
• Textbook Computer Networks A Systems Approach
  (Peterson and Davie, IIIrd ed)
• Goals To understand the design principles of the
  Internet. The course will follow a bottom-up
  approach, covering prominent link, network, and
  transport layer technologies, and the
  applications that shape the Internet.
• New this year Internet-wide measurements as
  class projects, using Planet-lab infrastructure!
• Grading
• Midterm 15
• Final 15
• Written assignments 15
• Projects 45 (15 for each of the three
  projects)
• Class participation/summaries 10
• Class Website http//www.cs.indiana.edu/classes/
  b538/

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L597 Structural Data Mining Modeling by Katy
Börner, SLIS

• SLIS graduate course, 3 credits
• Time Tue 1p-345p, LI036
• Format Lectures and 4-5 labs. Four class
  projects and two class presentations.
• This course
• Introduces students to major methods, theories,
  and applications of structural data mining and
  modeling.
• Covers elementary graph theory and matrix
  algebra, data collection, structural data mining,
  data modeling, and applications.
• Upon taking this course students will be able to
  analyze and describe real networks
• (power grids, WWW, social networks, etc.) as well
  as relevant phenomena such
• as disease propagation, search, organizational
  performance, social power,
• and the diffusion of innovations.
• Class Webpage http//ella.slis.indiana.edu/katy/
  L597

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L600 Networks Complex Systems talks Katy
Börner, SLIS

• SLIS graduate course, 1 credit
• Time Mon 6-7p in the Informatics Building_at_IUB,
  901 E. 10th St., Room 107
• Grading is based on the attendance of 8 talks
  (sign-up sheets will be provided) and a 4-5 page
  write-up that synergizes/aggregates major points
  made by a subset of the speakers to be submitted
  at the end of the semester.
• Class Webpage http//vw.indiana.edu/talks-fall05/