Dec. 22, 1995
Web Sites on Complexity
The Center for the Study of Complex Systems (PSCS) at UM
The Center for the Study of Complex Systems is a broadly interdisciplinary program at the University of Michigan designed to encourage and facilitate research and education in the general area of nonlinear, dynamical and adaptive systems. Participating faculty represent nearly every college of the University. The Program is based on the recognition that many different kinds of systems which include self-regulation, feedback or adaptation in their dynamics, may have a common underlying structure despite their apparent differences. Moreover, these deep structural similarities can be exploited to transer methods of analysis and understanding from one field to another. In addition to developing deeper understandings of specific systems, interdisciplinary approaches should help elucidate the general structure and behavior of complex systems, and move us toward a deeper appreciation of the general nature of such systems.
Santa Fe Institute
The current research agenda of SFI is simplicity, complexity, complex systems, and particularly complex adaptive systems. Even as the concepts involved in the "sciences of complexity" become well established elsewhere, this agenda, because of its breadth and because of the great variety of important scientific problems those concepts comprise, may endure for decades.
Santa Fe Institute Complex Systems Summer School
The school offers graduate students and postdoctoral scientists an introduction to the study of complex behavior in mathematical, physical and living systems. The four-week program features intensive tool-kit introductions to basic topics; week-long lecture courses on selected subjects, seminars, and computer lab workshops. A highly interactive format encourages group and individual research projects. Participants are expected to have graduate level training in one of the mathematical, physical, biological or information sciences. It is expected that students will attend the program for its full duration. June 2-28, 1996. Application deadline is February 2, 1996.
Computational Economic Modeling (including Computational Economics Summer School)
The Economics Program at the Santa Fe Institute is pleased to announce the second annual Graduate Workshop in Computational Economics. The workshop will bring together a group of advanced graduate students and a small faculty for an intensive two week study of computational economics. The workshop will consist of lectures by faculty, special topic seminars by members of the Santa Fe Institute, and presentations of work in progress by graduate student participants. The primary goal of the summer workshop is to assist graduate students pursuing research agendas which include a computational component. A significant portion of the workshop will be devoted to analyzing and improving research being conducted by the graduate student participants.
June 22-July 7, 1996. Application deadline is April 5, 1996.
The Swarm Simulation System
Swarm is a multi-agent simulation software platform for the study of complex adaptive systems. In the Swarm system the basic unit of simulation is the "swarm," a collection of agents executing a schedule of events. Swarm accommodates multi-level modeling approaches in which agents can be composed of swarms of other agents in nested hierarchies. Swarm schedules support hierarchies of time management yielding a natural model of concurrency and a straightforward path to parallel implementation. Swarm is currently under development; an alpha version is expected in early 1995, a beta version in the summer of '95, and a full, free source code release in the fall of '95.
StarLogo is a programmable modeling environment for exploring the behaviors of decentralized systems, such as bird flocks, traffic jams, and ant colonies. It is designed especially for use by students.
Urban Simulation (Scott Page and student implementation)
Game of Life
Includes lots of stuff on Conway's Game of Life, including free software packages for different operating systems and browsers.
Evolutionary Computation and Artificial Life
Evolutionary computation and artificial life are two relatively new areas of science which are both growing fast and gaining acceptance. Some people feel that artificial life and evolutionary computation are distinct areas with little overlap except that occasionaly artificial life researchers use evolutionary computation techniques like genetic algorithms. Personally, I feel that artificial life and evolutionary computation are very closely related. While it is possible to do artificial life without touching evolution, more and more the work done gains its success from evolving artificial creatures. Evolutionary computation is just an abstracted form of artificial life, for evolutionary computation struggles with the same ideas as artificial life: deciding how to represent "solutions" to an environment, deciding which "solutions" get to reproduce, deciding how things reproduce, and deciding which things die in the environment.
Artificial Life (Alife) is a rapidly growing field of scientific research linking biology and computer science. It seeks to understand how life-like processes can be embodied in computer programs. Advances in this area promise to illuminate fundamental
questions both in biology ("What is life?") and in Computer Science ("How to make robust and adaptable computer programs?").
Genetic Algorithms (GAs) were developed by Prof. John Holland and his students at the University of Michigan during the 1960s and 1970s. Essentially, they are a method of "breeding" computer programs and solutions to optimization or search problems by means of simulated evolution. Processes loosely based on natural selection, crossover, and mutation are repeatedly applied to a population of binary strings which represent potential solutions. Over time, the number of above-average individuals increases, and highly-fit building blocks are combined from several fit individuals to find good solutions to the problem at hand.
The Pascal source code for the simple GA (SGA) and simple classifier system (SCS) from David E. Goldberg's text "GAs in Search, Optimization, and Machine Learning" are available on the net at the following site. There's also some C, C++, and Lisp stuff too, for the sake of diversity.
Agent Theories, Architectures, and Languages
(Here is information about a workshop to be held in Budapest in August 1996. It gives an example of how computer scientists view agent-based modeling.)
The emergence of intelligent agent technology is one of the most exciting and important events to occur in computer science during the 1990s. It is now widely accepted that this technology will play a central role in the development of complex distributed systems, networked information systems, and computer interfaces during the twenty-first century. The aim of this workshop is to bring together researchers interested in the agent-level, micro aspects of this emerging technology. Specifically, the workshop will address such issues as the specification of agents via agent theories, agent architectures and decision-making, methodologies and languages for realising agents, and software tools for programming and experimenting with agents. In particular, the workshop will focus on the link between agent theories and the realisation of such theories using software architectures or languages. Issues such as agent communication languages also fall within the scope of the workshop.
University of Michigan Center for the Study of Complex Systems
Revised November 4, 1996.