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International Conference on Complex Systems (ICCS2006)

Teaching emergence and evolution simultaneously through simulated breeding of artificial swarm behaviors

Hiroki Sayama
Department of Bioengineering, Binghamton University, SUNY

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     Last modified: August 10, 2006

Abstract
Teaching emergence and evolution simultaneously through simulated breeding of artificial swarm behaviors
Hiroki Sayama

Emergence and evolution are the two most important concepts that account for how complex systems may self-organize. These concepts are often treated as related but somewhat separate subjects in typical educational settings, where they are taught using different examples, models and/or tools. In real complex systems, however, they are deeply intertwined to each other at a wide range of scales. It is therefore important for students to acquire a more intuitive and integrated understanding of these concepts and their linkages.

To address the above need in teaching complex systems, we developed a simple simulation tool "BoidsSB", which applies an interactive simulated breeding method to evolve populations of Craig Reynold's Boids system. In BoidsSB, each set of parameter settings that describe local interaction rules among individuals in a swarm is considered as a higher-level individual. The user manually evolves collective behavior of artificial agents by repeatedly selecting his/her preferred behavior as a parent of the next generation.

We used this tool as part of teaching materials of the course "Mathematical Modeling and Simulation" offered to engineering-major junior students in the Department of Human Communication at the University of Electro-Communications, Japan, during the Spring semester 2005. As a result, students actively engaged in the simulated breeding processes and voluntarily evolved a rich variety of swarm behaviors that were not initially anticipated. In the responses from the participating students were a number of noticeable comments on their evoked interest in the emergence of global collective dynamics out of local interaction rules, and on their admiration for the power of evolution that gives rise to nontrivial outcomes through repetition of simple processes. The fact that these comments were all obtained from a single simulation tool indicates the effectiveness of our approach.




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