Complex Adaptive Systems Course
Instructor: Dr. Ivan Garibay, UT-556, 2-1163, firstname.lastname@example.org
Class Time and Location: TR 3:00 PM – 4:15 PM, ENGR 383
Class website: http://ivan.research.ucf.edu/classes/CAP6675_Fall2012/
Complex adaptive systems (CAS) are a broad class of systems consisting of multiple interacting adaptive agents. These systems, which span a wide range of disciplines, have a number of characteristics in common. They are large distributed systems consisting of many self-similar components that interact and adapt. These interactions among the distributed components are self-organizing and produce emergent collective behavior in the system as a whole. CAS tend to be difficult to analyze using traditional analytical models. Agent-based models have been shown to be effective methods for studying CAS. This course will introduce the basic definitions of CAS, discuss example cases of CAS and their features, and implement and analyze computational simulations of CAS.
- Cellular automata
- Social systems
- Evolution of cooperation
- Social networks
- Agent-Based Computational Economics
This course will be structured as follows:
- Two papers will be assigned each week. You will be asked to read the papers and write a one-page summary/critique/comparison of the papers each week. These summaries will make up 15% of your final grade. Late summaries will not be accepted. You may drop two summaries.
- Each week two students will be asked to present the papers for that week to the class in an oral presentation. This presentation will include summarizing the paper and leading a discussion on the paper topic. These presentations will make up 20% of your final grade.
- You will have two homework projects during the first half of the course. All programming can be done in any programming language. These homeworks will be worth 25% of your final grade.
- Throughout the class you will work on a final research project. Before the middle of the course each student proposes an individual project. The proposed ideas are discussed in one or more individual meetings and one particular project is agreed upon between the instructor and the student. During the second half of the course, the student carries out the agreed project. The student writes up his/her work in a 8 to 10 pages paper (in the style of a conference paper). Towards the end of the semester all students will be ask to present their project to the class. The project due date, students must bring three extra copies of their project to be distributed to other three students to be anonymously peer reviewed. The last day of classes all students must bring their written reviews. Your final project grade will be partially based on the peer reviews of your work and the reviews that you write about other student’s projects. All projects will be compiled into a class book and published as an EECS Technical Report and also in the class website. Copies of this book will be distributed to all students. This final research project is worth 40% of your final grade.
Your final grade of this class will be determined as follows:
Paper Summaries (you may drop two) – 15%
Presentations – 20%
Homework – 25%
Final project, paper and presentation – 40%
- No make-ups will be given
- You may drop two lowest paper summary grades. Late summaries will not be accepted
- If you need to reschedule a paper presentation, please let me know at least two weeks before your originally scheduled presentation time. Otherwise, you will be responsible for the presentation at the originally scheduled time.
- Unless otherwise specified, all assignments are due at the beginning of class on the due date. Assignments turned in after class begins are considered to be late. Late homeworks and projects will have grades reduced by 10% per day.
- Homework and project code that does not compile or run will receive an automatic zero.
Cheating, plagiarism, and any other form of academic dishonesty will not be tolerated.
Plagiarism and paraphrasing are forms of cheating. Plagiarism is the presentation of others’ ideas and writings as your own. Paraphrasing is taking someone else’s sentence, changing a few words, and then presenting it as your own. Both are unacceptable in this class.
- Students are responsible for all material presented in class.
- Please do not bring cell phones or pagers to class.
Papers for this semester:
- Murray Gell-Mann (1995). What is Complexity? Complexity, 1:1.
- Yaneer Bar-Yam (2003). Chapter 0: Overview: The Dynamics of Complex Systems — Examples, Questions, Methods, and Concepts. Dynamics of Complex Systems. Westview Press.
- Marc H. V. Van Regenmortel (2004). Reductionism and complexity in molecular biology. European Molecular Biology Organization Reports, 5:11, 1016-1020.
- Stephen Wolfram (1983). Statistical mechanics of cellular automata. Reviews of Modern Physics, 55, 601-644.
- Melanie Mitchell, Peter T. Hraber, and James P. Crutchfield (1993). Revisiting the edge of chaos: Evolving cellular automata to perform computations. Complex Systems, 7, 89-130.
- Martin Gardner (1970). Mathematical games: The fantastic combinations of John Conway’s new solitaire game “Life”. Scientific American, 223: 120-123.
- Robert Axelrod (1980). More effective choice in the Prisoner’s Dilemma. Journal of Conflict Resolution, 24:3, 379-403.
- Martin A. Nowak and Robert M. May (1993). The spatial dilemmas of evolution. International Journal of Bifurcation and Chaos, 3:1, 35-78.
- Marco Dorigo, V. Maniezzo, and A. Colorni (1996). The ant system: Optimization by a colony of cooperating agents. Transactions on Systems, Man, and Cybernetics, Part B, 26:1, 29-41.
- Fabien Ravary, Emmanuel Lecoutey, Gwenael Kaminski, Nicolas Chaline, and Pierre Jaisson (2007). Individual experience alone can generate lasting division of labor in ants. Current Biology, 17, 1308-1312.
- Madeleine Beekman, David J. T. Sumpter, and Francis L. W. Ratnieks (2001). Phase transition between disordered and ordered foraging in Pharaoh’s ants. Proceedings of the National Academies of Science, 98:17, 9703-9706.
- Julia C. Jones, Mary R. Myerscough, Sonia Graham, and Benjamin P. Oldroyd (2004). Honey bee nest thermoregulation: Diversity promotes stability. Science, 305, 402-404.
- Anja Weidenmuller, Christoph Kleineidam, and Jurgen Tautz (2002). Collective control of nest climate parameters in bumblebee colonies. Animal Behavior, 63, 1065-1071.
- Albert-Laszlo Barabasi and Reka Albert (1999). Emergence of scaling in random networks. Science, 286, 509-512.
- Duncan J. Watts and Steven H. Strogatz (1998). Collective dynamics of ‘small-world’ networks. Nature, 393, 440-442.
- D. Challet and Y. C. Zhang (1997). Emergence of cooperation and organization in an evolutionary game. Physica A, 246, 407-418.
- Garrett Hardin (1968). The tragedy of the commons. Science, 162: 3859, 1243-1248.
- Terence Soule and Robert B. Heckendorn (2007). Evolutionary optimization of cooperative heterogensous teams. In the Proceedings of the SPIE: Evolutionary and Bio-inspired Computation: Theory and Applications, Volume 6563.
- E. T. Lofgren and N. H. Fefferman (2007). The untapped potential of virtual game worlds to shed light on real world epidemics. The Lancet Infectious Diseases, 7:9, 625-629.
- Shigeru Kondo (2002). The reaction-diffusion system: a mechanism for autonomous pattern formation in the animal ski. Genes to Cells, 7, 535-541.